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KennethCukier_2014S-_大数据好处多_
America's favorite pie is? 观察一个癌症活检组织
Audience: Apple. Kenneth Cukier: Apple. Of course it is. 观众:苹果派Kenneth Cukier:苹果派 毋庸置疑
How do we know it? 我们是怎么知道的？
Because of data. 因为数据
You look at supermarket sales. 当你观察超市的销售数据
You look at supermarket sales of 30-centimeter pies that are frozen, and apple wins, no contest. 会发现超市销售的30厘米冷冻馅饼中 苹果派胜出, 毫无悬念
The majority of the sales are apple. 绝大多数的销售份额就是来自苹果派
majority:n.大部分:大多数:多数票:成年人:
But then supermarkets started selling smaller, 11-centimeter pies, and suddenly, apple fell to fourth or fifth place. 但是之后超市开始销售 比较小的11厘米的馅饼 突然间苹果派的销量下降到了第4或第5名
Why? What happened? 为什么？怎么了？
Okay, think about it. 好, 想象一下
When you buy a 30-centimeter pie, the whole family has to agree, and apple is everyone's second favorite. 当你准备买一个30厘米的馅饼时 全家都不得不同意(选择苹果派馅饼) 虽然苹果派只是每个人的次选项
(Laughter) （笑声）
But when you buy an individual 11-centimeter pie, you can buy the one that you want. 但当你给自己选一个11厘米馅饼时 你可以买你最爱吃的口味
individual:n.个人;有个性的人;adj.单独的;个别的;
You can get your first choice. 你会选你的首选项
You have more data. 你有了更多数据
You can see something that you couldn't see when you only had smaller amounts of it. 你可以知道些事情 这些事情在你只有少量数据时 你是无法知道的
Now, the point here is that more data doesn't just let us see more, more of the same thing we were looking at. 这里, 关键的是更多的数据 不单单让我们知道更多 知道更多我们正在关注的同样事物
More data allows us to see new. 更多的数据使我们能了解新的事情
It allows us to see better. 让我们更好地了解
It allows us to see different. 让我们有不同的视角
In this case, it allows us to see what America's favorite pie is: not apple. 在这个例子里 更多的数据让我们知道 美国人最喜欢的馅饼 不是苹果派
Now, you probably all have heard the term big data. 你或许听说过大数据这个词
In fact, you're probably sick of hearing the term big data. 事实上, 你可能对这个词 已经心生厌恶
It is true that there is a lot of hype around the term, and that is very unfortunate, because big data is an extremely important tool by which society is going to advance. 确实, 大数据受到了空前的宣传炒作 这很不应该 因为大数据是一个非常重要的工具 社会将由此而不断进步
hype:n.大肆宣传;皮下注射;vt.大肆宣传;使…兴奋; extremely:adv.非常,极其;极端地;
In the past, we used to look at small data and think about what it would mean to try to understand the world, and now we have a lot more of it, more than we ever could before. 过去我们习惯于处理小数据 思考这些小数据的意义 并以此来了解世界 现在我们有很多很多的数据 数据量前所未有的巨大
What we find is that when we have a large body of data, we can fundamentally do things that we couldn't do when we only had smaller amounts. 当我们掌握海量数据时 我们可以做一些事 一些在只有较少数据时不可能办到的事
fundamentally:adv.从根本上;基础地;重要地
Big data is important, and big data is new, and when you think about it, the only way this planet is going to deal with its global challenges — to feed people, supply them with medical care, supply them with energy, electricity , and to make sure they're not burnt to a crisp because of global warming — is because of the effective use of data. 大数据很重要, 它也是一个新兴事物 想象一下 能够帮助我们应对 世界性难题 像食物短缺 医疗短缺 能源短缺 电力短缺 还有确保人类家园 不会因为全球变暖而生灵涂炭 的唯一办法是有效利用大数据
electricity:n.电力;电流;强烈的紧张情绪; crisp:adj.脆的;新鲜的;易碎的;v.使卷曲;使发脆;n.松脆物;油炸马铃薯片; global warming:n.全球(气候)变暖;地球大气层变暖; effective:adj.有效的,起作用的;实际的,实在的;给人深刻印象;
So what is new about big data? What is the big deal? 那么大数据新在何处, 重在何处呢？
Well, to answer that question, let's think about what information looked like, physically looked like in the past. 为了回答这个问题, 让我们看一下 信息看上去是什么样的 信息在以前是什么样的
In 1908, on the island of Crete, archaeologists discovered a clay disc. 1908年在克里特岛上(注:位于地中海 为希腊第一大岛) 考古学家发现了一个粘土做的盘子
archaeologists:n.[古]考古学家(archaeologist的复数); clay:n.黏土;陶土;
They dated it from 2000 B.C., so it's 4,000 years old. 这是个公元前2000年的盘子距今约有4000年的历史
Now, there's inscriptions on this disc, but we actually don't know what it means. 盘子上有铭文 但是我们不知道它们是什么意思
inscriptions:n.铭文;碑文;题字(inscription的复数);
It's a complete mystery, but the point is that this is what information used to look like 4,000 years ago. 这完全是个谜团 但这就是4000年前 信息的样子
This is how society stored and transmitted information. 这就是当时社会 存储和传递信息的方式
transmitted:v.传送;输送;发射;播送;传播;传染;(transmit的过去分词和过去式)
Now, society hasn't advanced all that much. 现代社会也没有什么很大的进步
advanced:adj.先进的; v.前进; (advance的过去式和过去分词形式)
We still store information on discs, but now we can store a lot more information, more than ever before. 我们还是把数据存储在盘中（注:指磁盘) 但我们可以存储更多的信息 远远超过以前的信息容量
Searching it is easier. Copying it easier. 这些信息搜索和复制起来更简单
Sharing it is easier. Processing it is easier. 分享和处理起来也更便捷
Processing:v.加工;处理;审核;数据处理;v.列队行进;缓缓前进;(process的现在分词)
And what we can do is we can reuse this information for uses that we never even imagined when we first collected the data. 我们也可以重新利用这些数据 一些我们当初收集的时候 从来没有料想过的用途
In this respect, the data has gone from a stock to a flow, from something that is stationary and static to something that is fluid and dynamic . 从这个方面来说 从静态的统计性的数据 变成动态的数据流
stock:n.股票; v.库存; adj.老一套的; stationary:adj.固定的;静止的;定居的;常备军的;n.不动的人;驻军; static:adj.静止的; n.[物]静电(干扰); fluid:adj.流动的;流畅的;不固定的;n.流体;液体; dynamic:n.动力; adj.充满活力的;
There is, if you will, a liquidity to information. 这就是信息的流动性
liquidity:n.流动性;流动资产;[金融]偿债能力;
The disc that was discovered off of Crete that's 4,000 years old, is heavy, it doesn't store a lot of information, and that information is unchangeable . 克里特岛发现的粘土盘 有4000年的历史, 非常笨重 但它不能记录太多的信息 并且它所记录的信息是不能更改的
unchangeable:adj.不变的;不能改变的;安定的;
By contrast , all of the files that Edward Snowden took from the National Security Agency in the United States fits on a memory stick the size of a fingernail , and it can be shared at the speed of light. 与此相反 所获得的文件 可以放在一个 仅有指甲大小的存储盘里 并且可以以光速进行数据共享
contrast:n.对比;对照;反差;明显的差异;v.对比;对照;形成对比; Snowden:n.斯诺登(姓氏); Agency:n.代理,中介;代理处,经销处; United:adj.联合的; v.联合,团结; (unite的过去分词和过去式) memory stick:n.内存扩展棒(断电不会造成数据丢失); fingernail:n.手指甲;
More data. More. 更多数据 更多
Now, one reason why we have so much data in the world today is we are collecting things that we've always collected information on, but another reason why is we're taking things that have always been informational but have never been rendered into a data format and we are putting it into data. 今天我们有这么多数据的一个原因是 我们一直在收集信息 就像我们一直在做的一样 另一个原因是我们记录了 许多蕴含丰富信息的事物 但是从没把信息转换成数据形式 现在我们正在把信息转变成数据
informational:adj.情报的;报告的;新闻的; rendered:v.使成为;给予;提供;回报;递交;(render的过去分词和过去式)
Think, for example, the question of location . 举个例子, 定位问题
location:n.地方;地点;位置;定位
Take, for example, Martin Luther. 比如说马丁·路德
If we wanted to know in the 1500s where Martin Luther was, we would have to follow him at all times, maybe with a feathery quill and an inkwell , and record it, but now think about what it looks like today. 在16世纪 如果我们想知道 马丁·路德在哪里 我们必须一直跟着他 或许用羽毛笔和墨水 把这些情况记录下来 那现今是什么样的情形呢？
feathery:adj.柔软如羽毛的;生有羽毛的; quill:n.大翎毛;羽茎;(豪猪,刺猬的)刚毛;vt.刺穿; inkwell:n.墨水池;
You know that somewhere, probably in a telecommunications carrier's database, there is a spreadsheet or at least a database entry that records your information of where you've been at all times. 在某些地方 可能在电信运营商的数据库里 有个电子数据表或者至少一个数据目录 记录着所有关于你 任何时候在什么地点的信息
telecommunications:n.电信;电讯; spreadsheet:n.电子制表软件;电子数据表;试算表;
If you have a cell phone, and that cell phone has GPS, but even if it doesn't have GPS, it can record your information. 如果你有个手机 这个手机有GPS, 或者即使没有GPS 它还是可以记录你的信息
In this respect, location has been datafied. 从这方面来说, 位置信息被数据化了
Now think, for example, of the issue of posture , the way that you are all sitting right now, the way that you sit, the way that you sit, the way that you sit. 再举个例子, 关于姿势 你们现在坐着的姿势 你坐着的姿势 你坐着的姿势 你坐着的姿势
issue:n.重要议题;争论的问题;v.宣布;公布;发出;发行; posture:n.姿势;态度;看法;立场;处理方式;v.故作姿态;装样子
It's all different, and it's a function of your leg length and your back and the contours of your back, and if I were to put censors , maybe 100 censors into all of your chairs right now, 这些都不一样 这是一个关于腿长 你的背部和背部轮廓的函数 如果我现在放一些传感器 或许100个 在你的椅子里
contours:n.轮廓(contour的复数); v.画等高线; censors:监察官;
I could create an index that's fairly unique to you, sort of like a fingerprint , but it's not your finger. 我可以算出你的独一无二的参数 就像你的指纹 但不是针对你的手指
index:n.指标;指数;索引;指针;v.做索引;指出;编入索引中; fairly:adv.相当地;公平地;简直; unique:adj.独特的,稀罕的;[数]唯一的;n.独一无二的人或物; fingerprint:n.指纹;手印;vt.采指纹;
So what could we do with this? 那我们能用它来干什么呢？
Researchers in Tokyo are using it as a potential anti-theft device in cars. 东京的研究者把它 运用在一个汽车防盗设施的雏形上
potential:n.潜能;可能性;[电]电势;adj.潜在的;可能的;势的; anti-theft:防盗; device:n.装置;策略;图案;
The idea is that the carjacker sits behind the wheel, tries to stream off, but the car recognizes that a non-approved driver is behind the wheel, and maybe the engine just stops, unless you type in a password into the dashboard to say, "Hey, I have authorization to drive." Great. 它的设想是盗贼坐在驾驶座上 企图把车开走 但是汽车识别出 驾驶座上的是个未授权驾驶人 那汽车可能就会熄火 除非你在仪表盘上输入密码 来表明“我已获得授权”
carjacker:n.武力劫夺汽车;抢劫司机财物(carjacking的变形); recognizes:v.认识;认出;辨别出;承认;意识到;(recognize的第三人称单数) dashboard:n.汽车等的仪表板;马车等前部的挡泥板; authorization:n.授权,认可;批准,委任;
What if every single car in Europe had this technology in it? 如果欧洲的每辆汽车 都装备了这项技术会是怎样的情形？
What if:如果…怎么办?
What could we do then? 我们还能做些什么呢？
Maybe, if we aggregated the data, maybe we could identify telltale signs that best predict that a car accident is going to take place in the next five seconds. 或许如果我们整合数据 我们可以识别示警信号 对于在下一个五秒钟内 可能发生的意外做出最佳预判
aggregated:adj.聚合的;合计的; identify:v.识别:鉴定:确认:发现: telltale:adj.报警的;泄密的;搬弄是非的;n.迹象;指示器;搬弄是非者; predict:v.预报;预言;预告; take place:发生;举行;
And then what we will have datafied is driver fatigue , and the service would be when the car senses that the person slumps into that position, automatically knows, hey, set an internal alarm that would vibrate the steering wheel , honk inside to say, "Hey, wake up, pay more attention to the road." 我们也可以进行数据化的是 司机的疲劳度 当汽车侦测到司机的坐姿 倒成某一特定姿势时 这个设备感知到并发出车内警告 可能是震动方向盘或语音提示 “嗨,醒醒 集中精神在路况上”
fatigue:n.疲劳;劳累;厌倦;(金属或木材的)疲劳;v.疲劳;使疲乏;(士兵)担任杂役; slumps:vi.下降,衰落;倒下;n.衰退;暴跌;消沉;vt.使降低;使衰落;使倒下; automatically:adv.自动地;机械地;无意识地;adj.不经思索的; internal:n.内脏;本质;adj.内部的;里面的;体内的;(机构)内部的; vibrate:vi.振动;颤动;摇摆;踌躇;vt.使振动;使颤动; steering wheel:n.方向盘;(操)舵轮; honk:n.雁叫声;汽车喇叭声;v.发雁鸣或汽车喇叭声;按汽车喇叭;
These are the sorts of things we can do when we datafy more aspects of our lives. 这就是生活的更多方面数据化后 我们能做的事情
aspects:n.方面;相位;面貌(aspect的复数);
So what is the value of big data? 那么大数据的价值在哪里？
Well, think about it. 好 思考一下
You have more information. 你有了更多地信息
You can do things that you couldn't do before. 你可以做你以前不能做的事
One of the most impressive areas where this concept is taking place is in the area of machine learning. 在运用这个概念的领域里 让人印象最为最深刻的 是机器学习
impressive:adj.感人的;令人钦佩的;给人以深刻印象的;
Machine learning is a branch of artificial intelligence , which itself is a branch of computer science . 机器学习是人工智能的一个分支 人工智能又是计算机科学的一个分支
artificial intelligence:n.人工智能; computer science:n.计算机科学;
The general idea is that instead of instructing a computer what do do, we are going to simply throw data at the problem and tell the computer to figure it out for itself. 它的基本理念是 把关于某个问题的一堆数据扔给电脑 让电脑自己找出解决方案 而不是教电脑应该做什么
And it will help you understand it by seeing its origins . 通过机器学习的原型 可以帮助你来理解这个理念
origins:n.起源; (origin的复数)
In the 1950s, a computer scientist at IBM named Arthur Samuel liked to play checkers , so he wrote a computer program so he could play against the computer. 20世纪50年代IBM的计算机科学家 亚瑟·塞缪尔想玩跳棋 所以他写了个程序 这样他就可以和电脑来玩
checkers:n.收银员;检查程序;检验员;审核员;(checker的第三人称单数和复数)
He played. He won. 开始他下一盘 赢一盘
He played. He won. 下一盘 赢一盘
He played. He won, because the computer only knew what a legal move was. 下一盘 赢一盘 因为电脑只知道 规则允许怎样走
legal:adj.法律的;合法的;法定的;
Arthur Samuel knew something else. 亚瑟·塞缪尔还知道其他东西
Arthur Samuel knew strategy . 他知道下棋的策略
strategy:n.策略;行动计划;部署;战略;
So he wrote a small sub-program alongside it operating in the background, and all it did was score the probability that a given board configuration would likely lead to a winning board versus a losing board after every move. 所以他又写了一个附加程序 这个程序在后台运行 它的功能只是计算概率 在一个给定的棋局里 每走一步后 会获胜或者失败的概率
probability:n.可能性;机率;[数]或然率; configuration:n.配置;结构;外形; versus:prep.对;与...相对;对抗;
He plays the computer. He wins. 再和电脑下棋 还是下一盘 赢一盘
He plays the computer. He wins. 下一盘 赢一盘
He plays the computer. He wins. 下一盘 赢一盘
And then Arthur Samuel leaves the computer to play itself. 后来亚瑟让电脑 自己和自己下棋
It plays itself. It collects more data. 电脑自己玩的时候收集了更多的数据
It collects more data. It increases the accuracy of its prediction . 收集的数据越多, 预测的准确率就越高
accuracy:n.[数]精确度,准确性; prediction:n.预报;预言;
And then Arthur Samuel goes back to the computer and he plays it, and he loses, and he plays it, and he loses, and he plays it, and he loses, and Arthur Samuel has created a machine that surpasses his ability in a task that he taught it. 然后亚瑟又继续和电脑下棋 这次他下一盘 输一盘 下一盘 输一盘 下一盘 输一盘 亚瑟创造了一个机器 它的能力超越了亚瑟开始时所教给它的
surpasses:vt.超越;胜过,优于;非…所能办到或理解;
And this idea of machine learning is going everywhere. 机器学习的理念 现在已经随处可见
How do you think we have self-driving cars? 你们觉得无人驾驶汽车(关键的技术)是什么？
self-driving:自驾;
Are we any better off as a society enshrining all the rules of the road into software? 是不是把所有交通规则输入软件 就万事大吉了？不是
enshrining:vt.铭记,珍藏;把…置于神龛内;把…奉为神圣;
No. Memory is cheaper. No. 内存很便宜？不是
Algorithms are faster. No. Processors are better. No. 算法更快了 不是 处理器更强大了 不是
Processors:n.加工机(或工人);处理器;处理机;(processor的复数)
All of those things matter, but that's not why. 这些都有影响, 但不是真正的原因
It's because we changed the nature of the problem. 真正的原因是我们改变了问题的本质
We changed the nature of the problem from one in which we tried to overtly and explicitly explain to the computer how to drive to one in which we say, "Here's a lot of data around the vehicle . 我们把问题的本质从 试图明确无误地 教会电脑怎样驾驶 变成我们对电脑说 “这里有许多关于汽车的数据
overtly:adv.明显地;公开地,公然地; explicitly:adv.明确地;明白地; vehicle:n.[车辆]车辆;工具;交通工具;运载工具;传播媒介;媒介物;
You figure it out. 你自己搞定它
You figure it out that that is a traffic light , that that traffic light is red and not green, that that means that you need to stop and not go forward." 你知道那是交通信号灯 那是红灯不是绿灯 遇到红灯你必须停下来 不能往前走”
traffic light:交通灯
Machine learning is at the basis of many of the things that we do online: search engines, 机器学习是许多 网上在线应用的基础 搜索引擎
Amazon's personalization algorithm, computer translation, voice recognition systems. 亚马逊的个性化算法 电脑智能翻译 语音识别系统
personalization:n.个性化; recognition:n.识别;认识;承认;认可;
Researchers recently have looked at the question of biopsies , cancerous biopsies , and they've asked the computer to identify by looking at the data and survival rates to determine whether cells are actually cancerous or not, and sure enough, when you throw the data at it, through a machine-learning algorithm, the machine was able to identify the 12 telltale signs that best predict that this biopsy of the breast cancer cells are indeed cancerous. 研究者最近在研究 关于活组织检查的问题 关于肿瘤活组织检查 他们让电脑 通过 (历史) 数据和存活率 来判断这些细胞 是否是癌症细胞 果不其然 当你把数据交给电脑 电脑通过自主学习 可以寻找出 12个最佳的鉴别特征用来预测 乳腺癌细胞的活检切片 确实是癌症细胞
recently:adv.最近;新近; biopsies:活组织检查; cancerous:adj.癌的;生癌的;像癌的; survival:n.幸存,残存;幸存者,残存物; determine:v.决定;确定;测定;查明;形成;影响;裁决;安排; machine-learning:机器学习; biopsy:n.活组织检查;切片检查法;v.活组织检查;切片检查法;
The problem: The medical literature only knew nine of them. 问题是医学文献 只知道其中的九个鉴别特征
literature:n.文学;文献;文艺;著作;
Three of the traits were ones that people didn't need to look for, but that the machine spotted . 其他三个 人们不会去寻找 但是电脑把它们找了出来
traits:n.特性,特质,性格(trait的复数); spotted:adj.有花点的;有斑点的;v.看见;看出;发现;让步;(spot的过去分词和过去式)
Now, there are dark sides to big data as well. 大数据也有黑暗的一面
It will improve our lives, but there are problems that we need to be conscious of , and the first one is the idea that we may be punished for predictions , 它可以改善我们的生活 但也会带来一些我们需要注意的问题 首先就是 我们可能因为预测的结果而受到惩罚
improve:v.改进;改善; conscious of:意识到; predictions:n.预测,预言(prediction复数形式);
that the police may use big data for their purposes, a little bit like " Minority Report." 警察可能会用大数据来实现目标 有点像“少数派报告”
Minority:n.少数民族;少数派;未成年;adj.少数的;属于少数派的;
Now, it's a term called predictive policing, or algorithmic criminology , and the idea is that if we take a lot of data, for example where past crimes have been, we know where to send the patrols . 现在有个词叫做预见性监管 或者叫算法犯罪学 这个想法是如果我们掌握了大量数据 比如以往犯罪发生的地点 我们可以就知道把警力派到哪里
predictive:adj.预言性的;成为前兆的; algorithmic:adj.[数]算法的;规则系统的; criminology:n.犯罪学;刑事学; patrols:n.巡逻队;v.[军]巡逻,巡查(patrol的三单形式);
That makes sense, but the problem, of course, is that it's not simply going to stop on location data, it's going to go down to the level of the individual. 这很合理 但问题是 数据分析不会仅限于地点数据 它会进一步深入到个人层面
Why don't we use data about the person's high school transcript ? 为什么我们不去分析 某人的中学成绩单
transcript:n.成绩单;抄本,副本;文字记录;
Maybe we should use the fact that they're unemployed or not, their credit score, their web-surfing behavior, whether they're up late at night. 或者我们可以了解 他们的就职情况、信用记录 他们的上网行为 他们是否熬夜
unemployed:adj.失业的;下岗的;n.(集合词)失业者;
Their Fitbit , when it's able to identify biochemistries, will show that they have aggressive thoughts. 当可以通过健康腕带读取生化数据时 就可以知道他们是否有激进的想法
Fitbit:n.一家美国科技公司; aggressive:adj.侵略性的;好斗的;有进取心的;有闯劲的;
We may have algorithms that are likely to predict what we are about to do, and we may be held accountable before we've actually acted. 我们可以用算法来预测 我们将要做什么 可能有些事情还没做 我们就要承担责任
are about to:眼看就要;即将;正要;行将; accountable:adj.有责任的;有解释义务的;可解释的;
Privacy was the central challenge in a small data era. 个人隐私在小数据时代 是主要挑战
Privacy:n.隐私;秘密;隐居;隐居处;
In the big data age, the challenge will be safeguarding free will , moral choice, human volition , human agency. 在大数据时代 这个挑战将会成为保卫自由意愿 道德选择 、人类意志 人类的能动性
safeguarding:v.保护;保障;捍卫;(safeguard的现在分词) free will:n.自由意志; moral:n.寓意;品行;教益;adj.道德的;道义上的;道德上的;品行端正的; volition:n.意志,意志力;决断力;
There is another problem: 还有另一个问题
Big data is going to steal our jobs. 大数据会偷走我们的工作
Big data and algorithms are going to challenge white collar, professional knowledge work in the 21st century in the same way that factory automation and the assembly line challenged blue collar labor in the 20th century. 在21世纪 大数据和算法会威胁到 白领和需要专业知识的工作 就像在20世纪工厂自动化 和装配生产线的应用 威胁到了蓝领们的工作岗位
professional:adj.专业的;职业的;职业性的;n.专业人员;职业运动员; automation:n.自动化;自动操作; assembly line:na.装配线; blue collar:adj.穿蓝领工装的;体力劳动的;蓝领阶级;
Think about a lab technician who is looking through a microscope at a cancer biopsy and determining whether it's cancerous or not. 想象一下一个研究室技术员 他的工作就是通过一个显微镜 观察一个癌症活检组织 来判定它是不是癌症的
technician:n.技术员;技师;(艺术、体育等的)技巧精湛者; microscope:n.显微镜; determining:v.查明;测定;准确算出;决定;支配;裁决;(determine的现在分词)
The person went to university. 这个人上大学
The person buys property. 买房子
He or she votes. 他/她投票选举
He or she is a stakeholder in society. 他/她是这个社会的一份子
stakeholder:n.利益相关者;赌金保管者;
And that person's job, as well as an entire fleet of professionals like that person, is going to find that their jobs are radically changed or actually completely eliminated . 然后这个人的工作 还有其他 像他一样的专业人员 将会发现他们的工作被彻底改变了 或者彻底废除了
as well as:也;和…一样;不但…而且; fleet:n.舰队; v.浅; v.掠过; adj.跑得快的; professionals:n.[管理]专业人员(professional的复数); radically:adv.根本上;彻底地;以激进的方式; eliminated:v.排除;清除;消除;(比赛中)淘汰;消灭;(eliminate的过去式和过去分词)
Now, we like to think that technology creates jobs over a period of time after a short, temporary period of dislocation , and that is true for the frame of reference with which we all live, the Industrial Revolution , because that's precisely what happened. 我们一直以为 在短时或者暂时的就业调整期后 一段时间内科技会创造就业机会 这对于我们所处的参考系 工业革命来说就是这样 因为在工业革命时期事情就是这样的
temporary:adj.暂时的,临时的;n.临时工,临时雇员; dislocation:n.转位;混乱;[医]脱臼; frame of reference:n.(影响人理解和判断事物的)信仰; Industrial Revolution:n.工业革命;
But we forget something in that analysis : 但是我们忘记了一件事情
analysis:n.分析;分解;验定;
There are some categories of jobs that simply get eliminated and never come back. 有些类型的职业 已经彻底消失了并且再也不会回来
categories:n.(人或事物的)类别,种类(category的复数)
The Industrial Revolution wasn't very good if you were a horse. 如果你是一匹马 工业革命不是一件好事
So we're going to need to be careful and take big data and adjust it for our needs, our very human needs. 所以我们必须非常小心 根据我们的需求和整个人类的需求 来利用和适应大数据
adjust:v.调整;调节;适应;习惯;
We have to be the master of this technology, not its servant. 我们必须是技术的主人 而不是技术的仆人
We are just at the outset of the big data era, and honestly, we are not very good at handling all the data that we can now collect. 我们正在步入大数据时代 老实说, 我们并不能很好地 处理所有我们现在能够收集到的数据
outset:n.开始;开端;
It's not just a problem for the National Security Agency. 这不仅仅是国家安全局的问题
Businesses collect lots of data, and they misuse it too, and we need to get better at this, and this will take time. 许多企业也搜集并不恰当地使用数据 我们需要时间来纠正这个问题
misuse:vt.滥用;误用;虐待;n.滥用;误用;虐待;
It's a little bit like the challenge that was faced by primitive man and fire. 这有点像原始人类面对火时 所面临的挑战
primitive:adj.原始的,远古的;简单的,粗糙的;n.原始人;
This is a tool, but this is a tool that, unless we're careful, will burn us. 火是一种工具 但是如果使用不当就会引火烧身
Big data is going to transform how we live, how we work and how we think. 大数据即将改变我们的生活方式 我们的工作方式和思考方式
transform:v.使改变;使改观;使转换;n.[数]变换式;[化]反式;
It is going to help us manage our careers and lead lives of satisfaction and hope and happiness and health, but in the past, we've often looked at information technology and our eyes have only seen the T, the technology, the hardware , because that's what was physical . 它可以帮助我们管理事业 帮助我们过想要的满足、充满希望 幸福和健康的生活 但是在过去, 对于信息技术(IT) 我们经常只看到了T 就是技术、硬件 因为这是切实可见的东西
careers:n.职业(career的复数);事业;职业生涯;v.全速前进(career的三单形式); satisfaction:n.满意,满足;赔偿;乐事;赎罪; information technology:n.信息技术; hardware:n.计算机硬件;五金器具; physical:adj.[物]物理的;身体的;物质的;符合自然法则的;n.体格检查;
We now need to recast our gaze at the I, the information, which is less apparent , but in some ways a lot more important. 现在我们需要把目光放在 I 上 信息 它不是那么切实可见 但某种程度上却更加重要
recast:vt.重铸;彻底改动;n.重铸;重做的事物; gaze:v.凝视;注视;盯着;n.凝视;注视; apparent:adj.显然的;表面上的;
Humanity can finally learn from the information that it can collect, as part of our timeless quest to understand the world and our place in it, and that's why big data is a big deal . 在人类永无止境的探索过程中 我们可以从我们能收集的信息中 来了解这个世界 以及人类在这个世界中所处的地位 这就是为什么大数据非常重要
Humanity:n.人类;人道;仁慈;人文学科; finally:adv.终于;最终;(用于列举)最后;彻底地; timeless:adj.永恒的;不受时间影响的;不合时宜的; quest:n.追求;寻找;vi.追求;寻找;vt.探索; a big deal:na.要人;重要的事;
(Applause) （掌声）