工業(yè)設(shè)計外文翻譯---不需要設(shè)計師的設(shè)計

1、<p>　　Design Without Designers</p><p><b>　　網(wǎng)站截圖：</b></p><p>　　http://www.baidu.com/baidu?word=%B9%A4%D2%B5%C9%E8%BC%C6%D3%A2%CE%C4%CE%C4%CF%D7&tn=sogouie_1_dg</p><

2、;p><b>　　原文：</b></p><p>　　Design Without Designers</p><p>　　I will always remember my first introduction to the power of good product design. I was newly arrived at Apple, still le

3、arning the ways of business, when I was visited by a member of Apple's Industrial Design team. He showed me a foam mockup of a proposed product. "Wow," I said, "I want one! What is it?" </p>

4、<p>　　That experience brought home the power of design: I was excited and enthusiastic even before I knew what it was. This type of visceral "wow" response requires creative designers. It is subjective,

5、personal. Uh oh, this is not what engineers like to hear. If you can't put a number to it, it's not important. As a result, there is a trend to eliminate designers. Who needs them when we can simply test our way

6、to success? The excitement of powerful, captivating design is defined as irrelevant. Worse,</p><p>　　Don't believe me? Consider Google. In a well-publicized move, a senior designer at Google recently qui

7、t, stating that Google had no interest in or understanding of design. Google, it seems, relies primarily upon test results, not human skill or judgment. Want to know whether a design is effective? Try it out. Google can

8、quickly submit samples to millions of people in well-controlled trials, pitting one design against another, selecting the winner based upon number of clicks, or sales, or whateve</p><p>　　This procedure is h

9、ardly unique to Google. Amazon.com has long followed this practice. Years ago I was proudly informed that they no longer have debates about which design is best: they simply test them and use the data to decide. And this

10、, of course, is the approach used by the human-centered iterative design approach: prototype, test, revise.</p><p>　　Is this the future of design? Certainly there are many who believe so. This is a hot topic

11、 on the talk and seminar circuit. After all, the proponents ask reasonably, who could object to making decisions based upon data? </p><p>　　Two Types of Innovation: Incremental Improvements and New Concepts

12、In design—and almost all innovation, for that matter—there are at least two distinct forms. One is incremental improvement. In the manufacturing of products, companies assume that unit costs will continually decrease thr

13、ough continual, incremental improvements. A steady chain of incremental innovation enhances operations, the sourcing of parts and supply-chain management. The product design is continually tinkered with, adjusting</p&

14、gt;<p>　　The second form of design is what is generally taught in design, engineering and MBA courses on "breakthrough product innovation." Here is where new concepts get invented, new products defined,

15、and new businesses formed. This is the fun part of innovation. As a result, it is the arena that most designers and inventors wish to inhabit. But the risks are great: most new innovations fail. Successful innovations ca

16、n take decades to become accepted. As a result, the people who create the innovation a</p><p>　　In my Apple example, the designers were devising a new conception. In the case of Google and Amazon, the compan

17、ies are practicing incremental enhancement. They are two different activities. Note that the Apple product, like most new innovations, failed. Why? I return to this example later.</p><p>　　Both forms of inno

18、vation are necessary. The fight over data-driven design is misleading in that it uses the power of one method to deny the importance of the second. Data-driven design through testing is indeed effective at improving exis

19、ting products. But where did the idea for the product come from in the first place? From someone's creative mind. Testing is effective at enhancing an idea, but creative designers and inventors are required to come u

20、p with the idea.</p><p>　　Why Testing Is Both Essential and IncompleteData-driven design is "hill-climbing," a well-known algorithm for optimization. Imagine standing in the dark in an unknown, hi

21、lly terrain. How do you get to the top of the hill when you can't see? Test the immediate surroundings to determine which direction goes up the most steeply and take a step that way. Repeat until every direction lead

22、s to a lower level. </p><p>　　But what if the terrain has many hills? How would you know whether you are on the highest? Answer: you can't know. This is called the "local maximum" problem: you

23、can't tell if you are on highest hill (a global maximum) or just at the top of a small one.</p><p>　　When a computer does hill climbing on a mathematical space, it tries to avoid the problem of local max

24、ima by initiating climbs from numerous, different parts of the space being explored, selecting the highest of the separate attempts. This doesn't guarantee the very highest peak, but it can avoid being stuck on a low

25、-ranking one. This strategy is seldom available to a designer: it is difficult enough to come up with a single starting point, let alone multiple, different ones. So, refinement thro</p><p>　　Here is where c

26、reative people come in. Breakthroughs occur when a person restructures the problem, thereby recognizing that one is exploring the wrong space. This is the creative side of design and invention. Incremental enhancements w

27、ill not get us there.</p><p>　　Barriers to Great InnovationDramatic new innovation has some fundamental characteristics that make it inappropriate for judgment through testing. People resist novelty. Behavi

28、or tends to be conservative. New technologies and new methods of doing things usually take decades to be accepted - sometimes multiple decades. But the testing methods all assume that one can make a change, try it out, a

29、nd immediately determine if it is better than what is currently available. </p><p>　　There is no known way to tell if a radical new idea will eventually be successful. Here is where great leadership and cour

30、age is required. History tells us of many people who persevered for long periods in the face of repeated rejection before their idea was accepted, often to the point that after success, people could not imagine how they

31、got along without it before. History also tells us of many people who persevered yet never were able to succeed. It is proper to be skeptical of radical new i</p><p>　　In the early years of an idea, it might

32、 not be accepted because the technology isn't ready, or because there is a lot more optimization still to be done, or because the audience isn't ready. Or because it is a bad idea. It is difficult to determine wh

33、ich of those reasons dominates. The task only becomes easy in hindsight, long after it becomes established. </p><p>　　These long periods between formation and initial implementation of a novel idea and its e

34、ventual determination of success or failure in the marketplace is what defeats those who wish to use evidence as a decision criterion for following a new direction. Even if a superior way of doing something has been foun

35、d, the automated test process will probably reject it, not because the idea is inferior, but because it cannot wait decades for the answer. Those who look only at test results will miss the l</p><p>　　Of cou

36、rse there are sound business reasons why ignoring potentially superior approaches might be a wise decision. After all, if the audience is not ready for the new approach, it would initially fail in the marketplace. That i

37、s true, in the short run. But to prosper in the future, the best approach would be to develop and commercialize the new idea to get marketplace experience, to begin the optimization process, and to develop the customer b

38、ase. At the same time one is preparing the company for</p><p>　　Gestural, multi-touch interfaces for screen-driven devices and computer games are good examples. Are these a brilliant new innovation? Brillian

39、t? Yes. New? Absolutely not. Multi-touch devices were in research labs for almost three decades before the first successful mass-produced products. I saw gestures demonstrated over two decades ago. New ideas take conside

40、rable time to reach success in the marketplace. If an idea is commercialized too soon, the result is usually failure (and a large loss of</p><p>　　This is precisely what the Apple designer of my opening para

41、graph had done. What I was shown was a portable computer designed for schoolchildren with a form factor unlike anything I had ever seen before. It was wonderful, and even to my normally critical eye, it looked like a per

42、fect fit for the purpose and audience. Alas, the product got caught in a political fight between warring Apple divisions. Although it was eventually released into the marketplace, the fight crippled its integrity and it

43、</p><p>　　The resistance of a company to new innovations is well founded. It is expensive to develop a new product line with unknown profitability. Moreover, existing product divisions will be concerned that

44、 the new product will disrupt existing sales (this is called "cannibalization"). These fears are often correct. This is a classic case of what is good for the company being bad for an existing division, which m

45、eans bad for the promotion and reward opportunities for the existing division. Is it a wonder</p><p>　　The FutureAutomated data-driven processes will slowly make more and more inroads into the space now occ

46、upied by human designers. New approaches to computer-generated creativity such as genetic algorithms, knowledge-intensive systems, and others will start taking over the creative aspect of design. This is happening in man

47、y other fields, whether it be medical diagnosis or engineering design. </p><p>　　We will get more design without designers, but primarily of the enhancement, refinement, and optimization of existing concepts

48、. Even where new creative artificial systems are developed, whether by neural networks, genetic algorithms, or some yet undiscovered method, any new concept will still face the hurdle of overcoming the slow adoption rate

49、 of people and of overcoming the complex psychological, social, and political needs of people. To do this, we need creative designers, creative business p</p><p>　　Design without designers? Those who dislike

50、 the ambiguity and uncertainty of human judgments, with its uncertain track record and contradictory statements will try to abolish the human element in favor of the certainty that numbers and data appear to offer. But t

51、hose who want the big gains that creative judgment can produce will follow their own judgment. The first case will bring about the small, continual improvements that have contributed greatly to the increased productivity

52、 and lowering of </p><p><b>　　譯文</b></p><p><b>　　不需要設(shè)計師的設(shè)計</b></p><p><b>　　唐·諾曼</b></p><p>　　我永遠也不會忘記我第一次向人們介紹優(yōu)秀產(chǎn)品設(shè)計的魅力的經(jīng)歷，那時候我

53、剛剛到蘋果公司，還在逐漸的學習工作上的事務。有一個蘋果工業(yè)設(shè)計小組的成員來我這里，向我展示了一個即將推出的產(chǎn)品的泡沫模型，“喔！”我說，“這是什么？我也想要個！”</p><p>　　那次經(jīng)歷讓我體驗到了設(shè)計的原始力量：當我還不知道他具體是什么之前我就已經(jīng)興奮不已，充滿熱情了。這種發(fā)自肺腑的回應離不開很有創(chuàng)意的設(shè)計師。這種想法很主觀，也很有個人感情色彩。哦，不過工程師們可不愿意聽到這些。如果你不能提供和它有關(guān)的數(shù)

54、據(jù)，它就沒什么了不起。這樣的結(jié)果是有一種不再需要設(shè)計師的趨勢。當我們可以簡單的測試我們的成功之路時，誰還需要設(shè)計師呢？令人充滿激情興奮無比的設(shè)計被看得無足輕重。更嚴重的是設(shè)計的初衷也岌岌可危了。</p><p>　　不相信吧？看看谷歌。最近谷歌的一位高級設(shè)計師有一次在公開場合宣稱，他們對設(shè)計不感興趣也不懂設(shè)計。據(jù)說，谷歌依靠最原始的測試結(jié)果而不是人類技巧和判斷。怎么知道一個設(shè)計是否成功呢？測試一下就可以了。谷歌會

55、迅速地把樣品發(fā)送給對照試驗中數(shù)以萬計的用戶，與其他的設(shè)計做個對比，然后選出優(yōu)勝者。他們可以靠點擊量，銷售量以及其他任何他們想要采用的客觀依據(jù)。什么顏色的制服最好？測試一下；哪種項目布置最合理？測試一下；哪種網(wǎng)頁排版最好呢？測試一下。</p><p>　　這可不是谷歌的專利，亞馬遜早就也這么做了。幾年前我很榮幸的被告知它們不再為哪個設(shè)計最好而爭論不休了，他們會測試一下然后用數(shù)據(jù)來決定。當然，這個也是以人為本的迭代設(shè)

56、計法采用的途徑：原型，試驗和修改。</p><p>　　這是設(shè)計的未來嗎？有很多人會真么認為。這是一個人們談論和研究交流的熱門話題，畢竟，支持者也有理有據(jù)：誰不想靠數(shù)據(jù)來做決定？</p><p>　　兩種類型的創(chuàng)新：不斷改善和全新的概念</p><p>　　在設(shè)計和幾乎所有改革中，其實都至少有兩種不同的類型。第一種是持續(xù)改進現(xiàn)有產(chǎn)品，在產(chǎn)品制造業(yè)中企業(yè)認為通過不斷地

57、改善和優(yōu)化單位成本也會持續(xù)的降低。不斷改善的帶來穩(wěn)定的利益鏈條又強化了操作，資源部門和產(chǎn)業(yè)鏈管理。產(chǎn)品的設(shè)計并沒有停止，改變一下外表，增加一些新的功能，不時的做些小的改動。新的產(chǎn)品都是對現(xiàn)有平臺很小的改動，每年都宣稱有了與眾不同的特征。有時候一些功能被去掉以用來支持一條新的，低成本的生產(chǎn)線，有時候很多功能又被組合或被添加上。產(chǎn)品不斷地改善，但基礎(chǔ)的平臺一直沒有改變。持續(xù)的設(shè)計和改進可沒有開發(fā)新概念或新理念那樣的引人矚目，但是它們很常見也

58、很重要。很多這樣的創(chuàng)新都是小規(guī)模的，但大多數(shù)都很成功。這就是企業(yè)們所說的“搖錢樹”：一條只需要很小改進的生產(chǎn)線，但是卻可以年復一年的有利可圖。</p><p>　　第二種類型的設(shè)計就是在設(shè)計，工程和MBA課程中經(jīng)常談論到的“有突破性的創(chuàng)新設(shè)計”。這里提出了全新的概念，新穎的產(chǎn)品定義和新型的商業(yè)模式，而且這些正是設(shè)計的樂趣所在。因此，這也是大多數(shù)的設(shè)計師和發(fā)明家樂意為之的地方。但是風險也很大：絕大多數(shù)的新發(fā)明都以失

59、敗告終。那些成功的設(shè)計發(fā)明往往需要數(shù)十年才得到了人們的認可，這樣的后果就是發(fā)明者不一定就是以它們獲利的人。</p><p>　　在我剛才提到的蘋果公司的例子中，設(shè)計者正在開發(fā)一種新概念產(chǎn)品。在谷歌和亞馬遜的例子中，這些公司在不斷地實踐著不斷的優(yōu)化。它們是兩種不同的行為，看看蘋果的產(chǎn)品，像大多數(shù)的新發(fā)明設(shè)計一樣失敗了。為什么呢？我一會兒再回到這個案例中。</p><p>　　這兩種設(shè)計都是很

60、有必要的。對數(shù)據(jù)主導型設(shè)計的激烈爭論誤導了人們，我們用前者的力量否定了后者的重要性。通過測試數(shù)據(jù)主導型設(shè)計對改進現(xiàn)有的產(chǎn)品很有效果。但是新產(chǎn)品最初的觀念有從何而來？一些人創(chuàng)造性的想法。測試可以高效的優(yōu)化一個想法，但是創(chuàng)造性的設(shè)計者和發(fā)明家卻需要有自己的想法。</p><p>　　為什么說測試既很有必要又不太完美</p><p>　　數(shù)據(jù)主導型的設(shè)計就是“爬山策略”，我們熟知的一種追求最優(yōu)化

61、的算法。假設(shè)你在黑夜里站在一個連綿起伏的山坡上，你什么也看不到，你怎么知道你就站在山坡的最高處？檢驗一下你周圍的環(huán)境，判斷哪個方向最陡峭，然后向這個方向邁進。這樣不斷的重復而知道每個方向就找到了最低的地方。</p><p>　　但是如果山坡上有很多的山峰又該怎么做呢？你怎么知道你是否已經(jīng)在最高的地方了？答案是你會不知道。這就是所謂的“局部最大值”問題：你不能區(qū)分你是在最高處呢還是只在一個小山坡的最高點。</

62、p><p>　　當計算機在數(shù)學空間里攀登時，它可以通過無數(shù)次的嘗試來探索不同的空間以避免局部最大化的難題。雖然這不能保證可以找到真正的最高點，但至少可以避免掉入低層次的行列中。對設(shè)計師來說這種戰(zhàn)略幾乎毫無用處。解決一個單一的起點就夠困難了，更不用說錯綜復雜的問題了。通過測試了改良設(shè)計通常能夠達到局部的最大利益。還有更好的解決辦法嗎（就是說，有沒有受益大于測試結(jié)果的情況）？測試不能告訴我們。</p>&l

63、t;p>　　這時候就得靠有創(chuàng)意的人了，他對問題的重新組合，于是就決定去看似錯誤的地方探索一下，新的突破就是這樣產(chǎn)生的。這正是設(shè)計發(fā)明創(chuàng)造性的一面，不斷地改良和完善不能讓我們擁有這樣的效果。</p><p><b>　　偉大發(fā)明的障礙</b></p><p>　　激動人心的新發(fā)明往往有一些基本的特點讓它們不適應由測試所做出的判斷。人們往往也不太喜歡獵奇，行動也很保

64、守。新的科技發(fā)明和方法往往經(jīng)過數(shù)十年或者更長才逐漸被人們認可接受。但是測試的法子都是假設(shè)某個東西很有前途值得一試，并來判斷它是否比正在使用的更好。我們沒有現(xiàn)成的方法判斷一個十分新奇的想法會獲得成功，這就需要出色的領(lǐng)導和鼓勵。歷史告訴我們很多在他們的想法被認可以前面臨長期不斷的抨擊的人們獲得成功以后就是這樣，沒有它以前，人們不知道是怎么如何度過的。歷史同樣也告訴我們還有很多人堅持不懈最終也沒有成功。對瘋狂想法的懷疑是可以理解的。在一個想法

65、的最初階段它沒有被人們接受很可能是因為技術(shù)還不太成熟，還需要很多的改善優(yōu)化也可能是因為消費者還沒有準備好。或者說它本來就是個壞主意，很難確定這是哪種原因決定的。在它實現(xiàn)很長時間以后，這才會變得可以預見。</p><p>　　一個想法最初形成實施到最終在商業(yè)上的成敗之間的漫長時間被當做是戰(zhàn)勝那些想把其作為展開新方向研究判斷標準的人的武器。即使做某件事比較好的方法已經(jīng)找到了，自動測試程序也會拒絕它，不是因為它不好，而

66、是我們不能為了這個答案等數(shù)十年。那些只看測試結(jié)果的人們將會失去豐厚的回報。當然，這也有為什么忽略潛在的新做法也可能是很明智的決定的合理商業(yè)因素。畢竟如果受眾還沒有為新的產(chǎn)品做好準備，它在市場上肯定會失敗。從短期看，這是正確的。但是為了長期的繁榮發(fā)展，最好的做法是開發(fā)和商業(yè)化新的想法去獲得市場經(jīng)驗，在開始優(yōu)化過程和發(fā)展客戶群。與此同時，還有一些在為公司做準備等待時機成熟。就是這樣，做著舊的產(chǎn)品但是在為新產(chǎn)品做準備。如果一個公司沒能夠掌握不

67、斷涌現(xiàn)的新方法，那么它的競爭者就會接管過去。這些公司往往成為新興的公司，現(xiàn)有的公司沒有注意到它們，因為它們所做的東西還沒有被廣泛接受，它們無論如何也不會對現(xiàn)有的業(yè)務構(gòu)成危險。明白了創(chuàng)造者所處的窘境了吧。</p><p>　　電腦游戲所用的觸摸屏和手勢控制屏就是個很的案例。這是個很優(yōu)秀的新發(fā)明吧？當然！新的？絕對不是。觸摸設(shè)置在首次作為成功大批量生產(chǎn)的產(chǎn)品之前在實驗室里已經(jīng)研究了30多年了。手勢控制的示范我20多年

68、前就見過了。新的想法需要相當長的時間才可以在市場上獲得成功。如果太早的商業(yè)化，其通常以失敗告終（還會有巨大的經(jīng)濟損失）。</p><p>　　這就是我開頭時說的那個蘋果設(shè)計師做的事情。他向我展示的是一個專門為學齡兒童設(shè)計的電腦，有一些我從未見過的特征。它真的很好，雖然我的眼光很挑剔。它很看起來很符合它的設(shè)計意圖和受眾。在阿拉斯加，這個產(chǎn)品在引起了決策層的激烈爭論。盡管它最終被決定投放市場，但論戰(zhàn)影響了它的整體運作

69、，沒有好好執(zhí)行，沒有得到很好的支持，也沒有很好的被市場化。</p><p>　　一個企業(yè)對全新的創(chuàng)新的抵制很容易建立，為一個不知道利潤如何的產(chǎn)品建立一條新的生產(chǎn)線代價很大。還有，由于新產(chǎn)品會打亂現(xiàn)有的產(chǎn)品銷售，現(xiàn)有的產(chǎn)品部門也會受到影響，這就是所謂的“品牌替換” 。這些擔心是正確的，這是一個很典型的情況，對公司有益的產(chǎn)品會不利于現(xiàn)有的部門，這也意味著不利于現(xiàn)有產(chǎn)品的提升和投資回報的機會。這是不是很糾結(jié)的企業(yè)堅守？

70、數(shù)據(jù)很清楚的告訴我們只有極少的創(chuàng)新確實很成功，大多數(shù)都失敗了，付出了高昂的代價。無論是它們沒有什么壓力還是年度報告危言聳聽，很多公司還是猶猶豫豫，抵制創(chuàng)新，這并不奇怪。保守點往往是很明智的。</p><p><b>　　未來</b></p><p>　　自動數(shù)據(jù)驅(qū)動的設(shè)計過程會慢慢得為設(shè)計師控制的領(lǐng)域帶來越來越多的危害。新的計算機控制創(chuàng)造力的趨勢，例如遺傳算法，集成化

71、系統(tǒng)，以及其他的未知的方法，將取代設(shè)計中的創(chuàng)新形態(tài)。這發(fā)生很多領(lǐng)域，不論是醫(yī)療診斷還是工程設(shè)計。</p><p>　　我們將會有更多的不需要設(shè)計師的設(shè)計，但這主要是鞏固，改進和優(yōu)化現(xiàn)有的概念。即使新的創(chuàng)新人工系統(tǒng)很發(fā)達，無論是通過神經(jīng)網(wǎng)絡(luò)還是基因算法或者其他未知的方法，任何新概念都必須面對克服人們緩慢的適應性和人們復雜的心理，社會，實際需求的障礙。為了解決這樣的問題，我們需要有創(chuàng)意的設(shè)計師，追求創(chuàng)新的商業(yè)人士和愿

72、意去沖破藩籬的冒險者。新的理念會被拒絕，偉大的創(chuàng)新的代價就是偉大的失敗。</p><p>　　沒有設(shè)計師的設(shè)計，那些人不喜歡人類判斷的含糊性和不確定性，他們試圖用測試的蹤跡不定的記錄和相對的穩(wěn)定性來廢除與確定性相關(guān)的人類因素，而由數(shù)字和數(shù)據(jù)來提供。但是那些認為可以自己可以做出創(chuàng)造性判斷的人們想獲得更大的收獲，他們聽從自己的判斷。前者可以帶來細微的，持續(xù)的改進，這可以使我們提高生產(chǎn)效率和降低技術(shù)成本；后者會帶來慘烈