I've been a journalist now since I was about 17, and it's an interesting industry to be in at the moment, because as you all know, there's a huge amount of upheaval going on in media, and most of you probably know this from the business angle, which is that the business model is pretty screwed, and as my grandfather would say, the profits have all been gobbled up by Google.
我從17歲開始當記者到現在 現在從事這行很有趣 因為正如各位所知道的 這個世代的媒體型態已有了很大的變動 在座的各位大概都知道 以商業的角度來看,這個産業已經玩完了 正如我爺爺所說的,利潤都被谷歌(Google)吃吞噬掉了
So it's a really interesting time to be a journalist, but the upheaval that I'm interested in is not on the output side. It's on the input side. It's concern with how we get information and how we gather the news. And that's changed, because we've had a huge shift in the balance of power from the news organizations to the audience. And the audience for such a long time was in a position where they didn't have any way of affecting news or making any change. They couldn't really connect. And that's changed irrevocably.
所以現在從事記者這行變得很有趣 不過在這遽變中,我比較感興趣的不是輸出端 而是輸入端 也就是我們取得資訊和新聞的方法 因為新聞媒體和觀眾之間的力量消長 已經有了大幅的改變 所以一切都變得不一樣了 過去長久以來 觀眾無法影響新聞或做任何改變 因為觀眾無法與媒體取得聯繫 不過現在已經産生了不可逆的轉變
My first connection with the news media was in 1984, the BBC had a one-day strike. I wasn't happy. I was angry. I couldn't see my cartoons. So I wrote a letter. And it's a very effective way of ending your hate mail: "Love Markham, Aged 4." Still works. I'm not sure if I had any impact on the one-day strike, but what I do know is that it took them three weeks to get back to me. And that was the round journey. It took that long for anyone to have any impact and get some feedback. And that's changed now because, as journalists, we interact in real time. We're not in a position where the audience is reacting to news. We're reacting to the audience, and we're actually relying on them. They're helping us find the news. They're helping us figure out what is the best angle to take and what is the stuff that they want to hear. So it's a real-time thing. It's much quicker. It's happening on a constant basis, and the journalist is always playing catch up.
我第一次聯繫新聞媒體是在1984年 當時BBC的員工罷工一天 當時我很不滿、很生氣,因為我看不到卡通 所以我寫了一封信 信件的結尾我是這樣寫的:「4歲的忠實觀眾Maekham」 我覺得這招真很有用,現在依然管用 我不知道我對那天的抗議事件是否帶來任何的影響 不過我知道的是,三個月後他們才回我的信 這就是信件往返的時間 一般人要花這麼久的時間才能産生影響力和收到回覆 不過這一切已經改變了 因為身為記者,我們的互動是即時的 我們的角色不再是等待觀眾的反應 我們要反應觀眾,因為我們依賴觀眾 觀眾幫我們挖掘新聞 幫我們找到報導的最佳角度,以及他們想要聽到的東西 這就是即時性,迅速且同步 身為記者就是要捕捉這些訊息
To give an example of how we rely on the audience, on the 5th of September in Costa Rica, an earthquake hit. It was a 7.6 magnitude. It was fairly big. And 60 seconds is the amount of time it took for it to travel 250 kilometers to Managua. So the ground shook in Managua 60 seconds after it hit the epicenter. Thirty seconds later, the first message went onto Twitter, and this was someone saying "temblor," which means earthquake. So 60 seconds was how long it took for the physical earthquake to travel. Thirty seconds later news of that earthquake had traveled all around the world, instantly. Everyone in the world, hypothetically, had the potential to know that an earthquake was happening in Managua. And that happened because this one person had a documentary instinct, which was to post a status update, which is what we all do now, so if something happens, we put our status update, or we post a photo, we post a video, and it all goes up into the cloud in a constant stream.
舉個例子讓大家知道我們有多依賴觀眾 9月5日哥斯大黎加發生地震 地震規模7.6,相當大 震波經過60秒後 抵達250公里外的馬納瓜 從震央發生地震到馬納瓜開始晃動隔了60秒 而推特(Twitter)在地震後30秒就出現了地震的消息 有人發文"temblor",意思就是地震 震波以物理的方式傳遞 需要花上60秒的時間 而地震的消息只花了30秒的時間 便同步傳遍世界各地 理論上每個人都有可能得知 馬納瓜發生地震的消息 這情況之所以會發生是因為這個人習慣作記錄 也就是更新個人的最新狀態 就像現在大家都會更新個人狀態一樣 不論發生什麼事,我們只要更新狀態、上傳照片和影片 這些資訊便不斷的透過雲端更新
And what that means is just constant, huge volumes of data going up. It's actually staggering. When you look at the numbers, every minute there are 72 more hours of video on YouTube. So that's, every second, more than an hour of video gets uploaded. And in photos, Instagram, 58 photos are uploaded to Instagram a second. More than three and a half thousand photos go up onto Facebook. So by the time I'm finished talking here, there'll be 864 more hours of video on Youtube than there were when I started, and two and a half million more photos on Facebook and Instagram than when I started.
這代表有很多的資料 無時無刻在更新 我們看看這些數據的確很嚇人 每分鍾有72小時的影片 上傳到YouTube 也就是說,每秒鐘有超過一個小時的影片上傳 圖片方面,每秒有58張照片上傳到Instagram 有超過3500張照片上傳到臉書(Facebook) 從我開始演說到結束這段期間 YouTube會多出864小時的影片 臉書和Instagram上會多出250萬張照片
So it's an interesting position to be in as a journalist, because we should have access to everything. Any event that happens anywhere in the world, I should be able to know about it pretty much instantaneously, as it happens, for free. And that goes for every single person in this room.
所以投入記者這一行很有趣 因為我們應該有管道可以知道所有的事 我應該可以即時得知世界各地發生的大事 這一切不用花到半毛錢 在座的各位也辦得到
The only problem is, when you have that much information, you have to find the good stuff, and that can be incredibly difficult when you're dealing with those volumes. And nowhere was this brought home more than during Hurricane Sandy. So what you had in Hurricane Sandy was a superstorm, the likes of which we hadn't seen for a long time, hitting the iPhone capital of the universe -- (Laughter) -- and you got volumes of media like we'd never seen before. And that meant that journalists had to deal with fakes, so we had to deal with old photos that were being reposted. We had to deal with composite images that were merging photos from previous storms. We had to deal with images from films like "The Day After Tomorrow." (Laughter) And we had to deal with images that were so realistic it was nearly difficult to tell if they were real at all. (Laughter)
問題是,當訊息太多時 要在這麼龐大的資訊量裡 要找出有用的訊息實在不容易 最明顯的例子就是颶風桑達(Sandy) 桑達是個超級颶風 這個百年難得一見的超級颶風 讓蘋果的股價嚴重受創(笑聲) 我們看到很多從未看過的媒體資訊 這表示記者得去求證 我們必須分辨那些照片是舊照重新上傳 那些是借用先前的颶風照片 合成出來的圖片 像是這張借用「明天過後」的照片(笑) 我們也得處理一些看起來非常真實 很難確定是否為真的照片 (笑)
But joking aside, there were images like this one from Instagram which was subjected to a grilling by journalists. They weren't really sure. It was filtered in Instagram. The lighting was questioned. Everything was questioned about it. And it turned out to be true. It was from Avenue C in downtown Manhattan, which was flooded. And the reason that they could tell that it was real was because they could get to the source, and in this case, these guys were New York food bloggers. They were well respected. They were known. So this one wasn't a debunk, it was actually something that they could prove. And that was the job of the journalist. It was filtering all this stuff. And you were, instead of going and finding the information and bringing it back to the reader, you were holding back the stuff that was potentially damaging.
玩笑歸玩笑,這張出現在Instagram的照片 讓很多記者爭論不休 沒人能確定,所以Instagram過濾了這張 有人質疑光影,幾乎每樣東西都有人質疑 結果後來發現這張照片是真的 這張是曼哈頓C街淹水的景象 這張照片之所以認定為真 是因為他們找到照片的來源 這張照片來自紐約的美食部落客 這群部落客很有名,頗受尊重 這張照片不是假的,而是經過證實的 記者的工作就是過濾訊息 記者的工作不是找資料 不是提供資料給讀者而已 還要把可能造成負面影響的東西剔除
And finding the source becomes more and more important -- finding the good source -- and Twitter is where most journalists now go. It's like the de facto real-time newswire, if you know how to use it, because there is so much on Twitter.
所以追朔可信的來源變得越來越重要 很多記者從推特(Twitter)尋找來源 如果運用得當,推特等同可靠的新聞網 因為上面有非常多的訊息
And a good example of how useful it can be but also how difficult was the Egyptian revolution in 2011. As a non-Arabic speaker, as someone who was looking from the outside, from Dublin, Twitter lists, and lists of good sources, people we could establish were credible, were really important. And how do you build a list like that from scratch? Well, it can be quite difficult, but you have to know what to look for. This visualization was done by an Italian academic. He's called André Pannison, and he basically took the Twitter conversation in Tahrir Square on the day that Hosni Mubarak would eventually resign, and the dots you can see are retweets, so when someone retweets a message, a connection is made between two dots, and the more times that message is retweeted by other people, the more you get to see these nodes, these connections being made. And it's an amazing way of visualizing the conversation, but what you get is hints at who is more interesting and who is worth investigating. And as the conversation grew and grew, it became more and more lively, and eventually you were left with this huge, big, rhythmic pointer of this conversation. You could find the nodes, though, and then you went, and you go, "Right, I've got to investigate these people. These are the ones that are obviously making sense. Let's see who they are."
2011年的埃及革命是個很好的例子 讓我們知道在推特上獲得訊息的優點與困難 身為來自都伯林(Dublin)的局外人 我不會講阿拉伯語 推特清單(Twitter List)有很多不錯的訊息來源 有很多可靠且重要的人可以加入清單 那我們要如何從無到有建立一個清單? 這不容易,因為你得找對方法 有位名為André Pannison的義大利學者 將訊息的聯結視覺化 他將穆巴拉克(Hosni Mubarak)下台那天 來自解放廣場(Tahrir Square)的對話集結起來 圖上的點代表推文 當有人推一則訊息時,兩個點之間會産生聯結 如果越多人推這則訊息 則産生的點越多,於是聯結就形成了 這種將對話視覺化的方法真的很神奇 可以從中知道那些人的推文比較有趣 那些人值得調查 隨荖互動越來越密集 狀態變得越來越熱絡 最後你就可以從中找到很多有規律的線索 你可以從點開始 然後想:「嗯,我想調查一下這些人, 這些消息看來很可靠, 我們來看看這些人是誰。」
Now in the deluge of information, this is where the real-time web gets really interesting for a journalist like myself, because we have more tools than ever to do that kind of investigation. And when you start digging into the sources, you can go further and further than you ever could before.
在一片資訊洪流中 這即時訊息網站對記者來說很有趣 因為我們更勝以往 擁有更多調查的工具 當你著手調查訊息來源的時候 你可以做到更深入的程度
Sometimes you come across a piece of content that is so compelling, you want to use it, you're dying to use it, but you're not 100 percent sure if you can because you don't know if the source is credible. You don't know if it's a scrape. You don't know if it's a re-upload. And you have to do that investigative work. And this video, which I'm going to let run through, was one we discovered a couple of weeks ago.
有時你會遇到很吸引人的題材 你非常非常想用 可是你無法百分之百確定是否能用 因為你不曉得來是否可信 你不知道訊息是否完整,是否為重新上傳的舊聞 所以你要做調查工作 接下來我要播的影片 是我們幾個禮拜前發現的
Video: Getting real windy in just a second.
影片:才一秒鐘風就變得很大
(Rain and wind sounds)
(實際風雨聲)
(Explosion) Oh, shit!
(爆炸聲)哇哩咧!
Markham Nolan: Okay, so now if you're a news producer, this is something you'd love to run with, because obviously, this is gold. You know? This is a fantastic reaction from someone, very genuine video that they've shot in their back garden. But how do you find if this person, if it's true, if it's faked, or if it's something that's old and that's been reposted?
Markham Nolan:如果你是新聞製作人 你一定會想播這段,因為真的很精彩 你知道嗎,這個人的反應實看來很真實 看起來真的是在自家後院拍的 不過你如何知道這個人是真是假? 或者是不是舊影片重新上傳?
So we set about going to work on this video, and the only thing that we had to go on was the username on the YouTube account. There was only one video posted to that account, and the username was Rita Krill. And we didn't know if Rita existed or if it was a fake name. But we started looking, and we used free Internet tools to do so. The first one was called Spokeo, which allowed us to look for Rita Krills. So we looked all over the U.S. We found them in New York, we found them in Pennsylvania, Nevada and Florida. So we went and we looked for a second free Internet tool called Wolfram Alpha, and we checked the weather reports for the day in which this video had been uploaded, and when we went through all those various cities, we found that in Florida, there were thunderstorms and rain on the day. So we went to the white pages, and we found, we looked through the Rita Krills in the phonebook, and we looked through a couple of different addresses, and that took us to Google Maps, where we found a house. And we found a house with a swimming pool that looked remarkably like Rita's. So we went back to the video, and we had to look for clues that we could cross-reference. So if you look in the video, there's the big umbrella, there's a white lilo in the pool, there are some unusually rounded edges in the swimming pool, and there's two trees in the background. And we went back to Google Maps, and we looked a little bit closer, and sure enough, there's the white lilo, there are the two trees, there's the umbrella. It's actually folded in this photo. Little bit of trickery. And there are the rounded edges on the swimming pool. So we were able to call Rita, clear the video, make sure that it had been shot, and then our clients were delighted because they were able to run it without being worried.
所以我們就去研究這段影片 我們唯一的線索是YouTube上的使用者名稱 這個帳號只有上傳一支影片 使用者名為Rita Krill 我們不知道Rita是不是確有其人,或者只是假名 不過我們仍藉由免費的網路工具尋找 我們首先使用Spokeo來尋找Rita Krills這個人 我們搜尋整個美國,結果發現紐約、 賓州、內華達州、佛州都有人叫作Rita Krills 所以我們接下去使用第二套免費工具 叫作Wolfram Alpha來查詢氣象報導 看看是否和影片拍攝上傳時的天氣吻合 我們查詢這幾個州的天氣 結果發現佛州當天有發生大雷雨 接下來我們打開電話簿 搜尋所有名為Rita Krills的資料 結果我們找到了幾個地址 接下去我們用谷歌地圖(Google Maps)找到了一間房子 這間房子有一個游泳池 看起來和影片中的很像,所以我們回頭看影片 找尋可能的線索交叉比對 影片中這裡有個雨傘 泳池中間有張白色的氣墊床 泳池的邊角是圓角 而且後院有兩棵樹 回到谷歌地圖拉近一點 的確有張白色的氣墊床 有兩棵樹和一支傘 這支傘在圖片裡是收合狀態 巧合的是泳池的邊角也是圓角 所以我們就打電話給Rita 確定影片是由她所拍攝的 結果她很開心,因為不用擔心別人的懷疑
Sometimes the search for truth, though, is a little bit less flippant, and it has much greater consequences. Syria has been really interesting for us, because obviously a lot of the time you're trying to debunk stuff that can be potentially war crime evidence, so this is where YouTube actually becomes the most important repository of information about what's going on in the world.
尋找真象的過程中 態度嚴謹一點會帶來理想的結果 我們一直對敘利亞很有興趣 因為當你想要揭露真象 挖掘戰爭罪行的可能證據時 YouTube可以讓我們知道世界上發生的事 儼然成了重要的資料寶庫
So this video, I'm not going to show you the whole thing, because it's quite gruesome, but you'll hear some of the sounds. This is from Hama. Video: (Shouting) And what this video shows, when you watch the whole thing through, is bloody bodies being taken out of a pickup truck and thrown off a bridge. The allegations were that these guys were Muslim Brotherhood and they were throwing Syrian Army officers' bodies off the bridge, and they were cursing and using blasphemous language, and there were lots of counterclaims about who they were, and whether or not they were what the video said it was.
這段影片因為內容太血惺 所以不全部播出來,不過仍可以聽到聲音 影片來自哈馬(Hama) 影片:(叫聲) 在完整的影片裡可以看到 這些人將一具血跡斑斑的屍體從貨車上搬下來 然後丟到橋下 據說這些人屬於穆斯林兄弟會(Muslim Brotherhood) 他們正把敘利亞官員的屍體丟下橋 他們不斷的用褻瀆的言語辱罵 不過也有人針對他們的身份提出反駁 認為他們並不是影片中說的那樣
So we talked to some sources in Hama who we had been back and forth with on Twitter, and we asked them about this, and the bridge was interesting to us because it was something we could identify. Three different sources said three different things about the bridge. They said, one, the bridge doesn't exist. Another one said the bridge does exist, but it's not in Hama. It's somewhere else. And the third one said, "I think the bridge does exist, but the dam upstream of the bridge was closed, so the river should actually have been dry, so this doesn't make sense." So that was the only one that gave us a clue. We looked through the video for other clues. We saw the distinctive railings, which we could use. We looked at the curbs. The curbs were throwing shadows south, so we could tell the bridge was running east-west across the river. It had black-and-white curbs. As we looked at the river itself, you could see there's a concrete stone on the west side. There's a cloud of blood. That's blood in the river. So the river is flowing south to north. That's what that tells me. And also, as you look away from the bridge, there's a divot on the left-hand side of the bank, and the river narrows.
所以我們問了幾位住在哈馬的人 我們之前常常在推特上往來 因為那座橋可能是線索,所以我們很有興趣 三個人有三種不同的說法 其中一個說根本沒這座橋 另一個說有這座橋,不過不在哈馬,而是在別處 第三個說:「我覺得有這座橋, 不過上游的水壩是關著的, 所以河道應該是乾的,這個看來不合理。」 這就是我們得到的唯一線索 我們再從影片中找尋其它的線索 我們看到特別的欄杆可以當作線索 路邊石壆的影子投射在南邊 所以這座橋是東西向跨越河流 石壆是黑白相間 從河流本身可以看出 西邊有水泥石塊,河面上有一片血 從這片血可以得知 河流的流向是由南向北 從橋上往下看 河岸的左邊有一片草皮 然後河道漸漸變窄
So onto Google Maps we go, and we start looking through literally every single bridge. We go to the dam that we talked about, we start just literally going through every time that road crosses the river, crossing off the bridges that don't match. We're looking for one that crosses east-west. And we get to Hama. We get all the way from the dam to Hama and there's no bridge. So we go a bit further. We switch to the satellite view, and we find another bridge, and everything starts to line up. The bridge looks like it's crossing the river east to west. So this could be our bridge. And we zoom right in. We start to see that it's got a median, so it's a two-lane bridge. And it's got the black-and-white curbs that we saw in the video, and as we click through it, you can see someone's uploaded photos to go with the map, which is very handy, so we click into the photos. And the photos start showing us more detail that we can cross-reference with the video. The first thing that we see is we see black-and-white curbing, which is handy because we've seen that before. We see the distinctive railing that we saw the guys throwing the bodies over. And we keep going through it until we're certain that this is our bridge.
回到谷歌地圖 我們逐一比對每座橋 我們從水壩開始尋找 我們找遍所有和道路交叉的河流 刪除不吻合的橋樑 我們尋找東西向的道路 我們從水壩一直找到哈馬 不過沒有看到橋 所以我們進一步用衛星模式尋找 我們找到另一座橋,於是線索開始串連起來 這座橋看起來像是東西向橫跨河流 看起來像是我們要找的橋 放大後可以看到有分隔島,所以這座橋是雙線道 而且路壆和影片中的一樣是黑白相間 點進去看可以看到很多人上傳的照片 地圖上多了這些照片很實用 點進去就可以看到照片 照片的細節可以用來和影片交叉比對 最先看到的是黑白相間的路壆 很容易辦識,因為我們先前已經看過了 我們可以看到造形獨特的欄杆 和丟人下去的那一幕一樣 我們繼續搜尋直到確定這就是我們要找的橋
So what does that tell me? I've got to go back now to my three sources and look at what they told me: the one who said the bridge didn't exist, the one who said the bridge wasn't in Hama, and the one guy who said, "Yes, the bridge does exist, but I'm not sure about the water levels." Number three is looking like the most truthful all of a sudden, and we've been able to find that out using some free Internet tools sitting in a cubicle in an office in Dublin in the space of 20 minutes. And that's part of the joy of this. Although the web is running like a torrent, there's so much information there that it's incredibly hard to sift and getting harder every day, if you use them intelligently, you can find out incredible information. Given a couple of clues, I could probably find out a lot of things about most of you in the audience that you might not like me finding out.
所以這代表什麼呢? 回頭看看那三個人講過的話 一個說沒這座橋 另一個說這座橋不在哈馬 最後一個說:「有這座橋,不過我不確定水位。」 第三個看起來最接近事實 我們只需坐在都柏林的辦公室 使用免費的網路工具 20分鐘就可以查到結果 這是調查工作的樂趣之一 雖然網路上的訊息像洪流一樣泛濫 要過濾這些訊息越來越不容易 不過只要善加利用就能夠得到有用的資訊 只要給我一點線索 也許我可以找到在座各位不想讓人知道的事情
But what it tells me is that, at a time when there's more -- there's a greater abundance of information than there ever has been, it's harder to filter, we have greater tools. We have free Internet tools that allow us, help us do this kind of investigation. We have algorithms that are smarter than ever before, and computers that are quicker than ever before.
這告訴我們 身處在資訊空前豐富的時代,雖然過瀘訊息變得更為困難 不過我們也擁有更多的工具 我們有免費的網路工具 可以幫我們進行調查工作 我們有更聰明的演算法 以及運算速度更快的電腦
But here's the thing. Algorithms are rules. They're binary. They're yes or no, they're black or white. Truth is never binary. Truth is a value. Truth is emotional, it's fluid, and above all, it's human. No matter how quick we get with computers, no matter how much information we have, you'll never be able to remove the human from the truth-seeking exercise, because in the end, it is a uniquely human trait. Thanks very much. (Applause)
不過要知道,演算法是以二進位為基礎的運算法則 只有是與非,黑與白 真象是一種價值觀,不能用二位元歸類 真象是有情感的、有變化的,最重要的是,真象是人性的 不論電腦速度進步得多快 不論你可以得到的訊息有多少 在追求真象的過程中,你用永遠無法將人排除在外 因為追求真象是人類獨有的特點 謝謝各位(掌聲)