采訪：張詩陽

耿百利教授是弗吉尼亞大學風景園林系系主任，曾任教于哈佛大學、路易斯安那州立大學、羅德島設(shè)計學院。他關(guān)注于計算機技術(shù)、人工智能在風景園林不同領(lǐng)域中的應(yīng)用，并開展了大量相關(guān)的研究、教學與實踐。他曾受邀參與在北京林業(yè)大學舉行的2019年世界風景園林師高峰論壇，《風景園林》雜志社有幸對耿百利教授進行了專訪。訪談中耿百利教授結(jié)合自己的大量研究，探討了計算機科學對于理解環(huán)境與生態(tài)系統(tǒng)、風景園林設(shè)計及教育的影響。以下是采訪全文。

LAJ：《風景園林》雜志社

Bradley：耿百利·坎特雷爾

LAJ：您的本科專業(yè)是計算機科學，而后在哈佛學習了風景園林。是什么原因讓您選擇了風景園林作為職業(yè)呢？

Bradley：這是一個非常好的問題。在北美很多人并不熟悉風景園林，直到他們以某種方式接觸它。在學習風景園林之前，我學習的是工作室藝術(shù)（studio-art）和計算機科學。我了解風景園林純屬偶然，起初我并不熟悉它，我熱愛植物、熱愛戶外，同時也喜歡電腦制圖。因此，當我發(fā)現(xiàn)風景園林可以將以上方面融合到一起時，我發(fā)現(xiàn)它完美地適合我。事實上，我是在一家植物種植公司了解到風景園林的，有人告訴我你可以用植物進行設(shè)計，所以我開始接觸風景園林。

LAJ：我相信您的計算機背景對您近年來的風景園林研究有很大的影響。您更多地借助智能生態(tài)系統(tǒng)、數(shù)字模型等來實現(xiàn)自然的自主性，這與這些技術(shù)在建筑設(shè)計或城市規(guī)劃領(lǐng)域的應(yīng)用截然不同。您認為數(shù)字技術(shù)與風景園林融合的關(guān)鍵詞和特征是什么呢？

Bradley：我認為數(shù)字技術(shù)在建筑、規(guī)劃、甚至是工程領(lǐng)域的應(yīng)用多數(shù)時候是在尋找一個特定的答案，這與風景園林領(lǐng)域有著很大的不同。通常人們需要通過計算明確地了解到對象的本質(zhì)，從而找到最有效的方式來解決問題。然而，在風景園林以及環(huán)境設(shè)計領(lǐng)域，我們通常也運用計算機去了解系統(tǒng)的功能，但是人類與環(huán)境的相互作用是十分復雜的，包括生物的復雜性、其他物種以及所有類型的環(huán)境過程和功能，這些都不太容易進行運算。因而我們希望開發(fā)一種新的計算機應(yīng)用方式，其不僅能夠理解自然和環(huán)境過程的運轉(zhuǎn)模式，也能直接進行互動。所以，我認為最大的不同在于我們必須開展一對一的工作，逐一構(gòu)建模型并開展與環(huán)境的互動實驗。這些實驗使我們能夠得到環(huán)境的反饋信息，然后借助計算機來理解這些信息并開展行動。但這并不意味著我們必須了解全部，只是我們開始運用計算機的力量去與環(huán)境進行互動來進行學習。

LAJ：我注意到您的很多研究談到了人工智能，您認為當前人工智能在風景園林行業(yè)應(yīng)用的關(guān)鍵是什么？人工智能將在處理環(huán)境問題中扮演怎樣的角色呢？

Bradley：這是一個宏大的問題，可能會講述好幾個小時。目前我們對環(huán)境的理解通常取決于2個方面：一方面是環(huán)境的自身作用，比如樹木或者物種的自然生長，我們稱之為自然，或者野性；另一方面，我們自身也維護、建造或者設(shè)計環(huán)境，我們通常稱其為景觀，也就是說通過人類的介入來改造環(huán)境。我認為目前人工智能可以幫助我們思考如何來維持景觀和環(huán)境，將會用有一種智能維護的景觀，我們將創(chuàng)建一種新的環(huán)境類型，它具有高度的維持性，我們也許永遠不會真正地了解，但是把它看作是一種自然或者 野性。

因此，環(huán)境維持的方式以及我們與計算機智能的關(guān)系將發(fā)生根本的變化。有一件事情目前還沒有理解清楚，在我們利用機器學習了解景觀新事物的同時，我們目前還不能確切地了解它是如何完成它的過程的。我和張子豪（弗吉尼亞大學在讀博士研究生）都寫過相關(guān)的論文[1-2]，即第三類人工智能。我們屬于生物智能的一部分，但人類總喜歡把自己刨除在外，從而出現(xiàn)了人類智能，當然還有計算機智能（人工智能屬于其中的一部分）。這其中包含3個角色，我認為它們每一個都在我們理解如何將人工智能運用在社會或者風景園林時扮演著不同的角色。

LAJ：所以你說第3類智能不再是關(guān)于自然的？

Bradley：它已經(jīng)并且將會從根本上改變?nèi)藗兯伎甲匀坏姆绞健Ｓ械牡胤轿覀円呀?jīng)通過復雜的程序來維護它們，它們并非沒有受到影響，它們在持續(xù)發(fā)展，實際上有很多過程在變化。維持這種變化的智能不是人類智能，我們并不真正理解為什么電腦會這樣做，因為計算方面的東西對我們來說是未知的。因此這創(chuàng)造了一種新的關(guān)系和一個新的生態(tài)系統(tǒng)。

LAJ：從您的觀點來看，人工智能應(yīng)該作為風景園林的媒介來構(gòu)建連接人、自然和技術(shù)的框架系統(tǒng)。您能給我們介紹一下在這方面的實驗或?qū)嵺`嗎?

Bradley：考慮這個問題的一種方式是把許多因素結(jié)合在一起，因為人類把所有這些自然和技術(shù)，以及不斷發(fā)展的文化都聯(lián)系在一起。我們一直在尋找這樣做的方法，這是設(shè)計的核心。當人們做出這樣的努力時，我們會非常認同，因此通常它可能是生態(tài)的，但也可能不如美學重要。有一種奇怪的關(guān)系，設(shè)計師總是傾向于人性而非與我們關(guān)注的一致。設(shè)計會有很多其他目標，那么結(jié)果可能是我們開始為其他物種構(gòu)建其他類型的景觀，其中人類是次要的。它們有高度維持性，但是是為了服務(wù)其他物種。

LAJ：您認為人工智能的干預會對當前的風景園林設(shè)計過程產(chǎn)生怎樣的影響?

Bradley：我想我可能說了很多，簡短地說，我一直是在一個長期的視野里探討，也許20年以后。但在短期內(nèi)，我認為我們所看到的最大變化是以一種新的方式來思考景觀形式和景觀模式，這是我使用機器學習的主要方式。它是一種非常復雜的系統(tǒng)，機器學習可以在這些模式中找到相似之處，并開始思考形式的內(nèi)涵及其與其他系統(tǒng)的關(guān)系。美學的形式也許不同，但它們運轉(zhuǎn)方式都是相同的。機器學習可以幫助我們透過形式看到其中的內(nèi)涵。我認為在短期內(nèi)，它將改變我們的視角，從形式的研究轉(zhuǎn)向為現(xiàn)象的研究。

LAJ：所以您的意思是我們應(yīng)該決定我們應(yīng)該設(shè)計什么？

Bradley：為它設(shè)計一種新技術(shù)，對吧？它不只是我們看到的形式。

LAJ：它不僅是一種形式，更是一種策略或者其他方面。設(shè)計是一個復雜的過程，既包括科學的邏輯思維，也包括對場地的感性認知。您認為數(shù)字技術(shù)在環(huán)境感知或場所藝術(shù)性方面扮演什么角色?

Bradley：實際上我并不認為數(shù)字技術(shù)會帶來太大的改變。在某種程度上，我們?nèi)匀皇侨祟悾覀內(nèi)匀辉谟梦覀兊墓ぞ咭灶愃频姆绞竭M行設(shè)計，主要的區(qū)別是2個部分：一方面，數(shù)字設(shè)計的一個優(yōu)勢是速度，我們可以快速地進行篩選和生產(chǎn)；另一方面，我們可以進行更精確的分析。其缺點可能是會為我們帶來太多的選擇，并削弱實用性。所以我們必須敏銳地意識到，我們?nèi)匀恍枰趫龅刂薪⒁恍┣袑嵉穆?lián)系。數(shù)字化使得理解場地的物理屬性變得更加復雜，因而我們需要開發(fā)一種新的方式來精確地進行場地介入。

LAJ：最后，讓我們回到教育。風景園林教育中傳統(tǒng)的計算機技術(shù)教學更多地涉及軟件學習，如CAD、Rhino等。在計算機相關(guān)技術(shù)快速發(fā)展和人工智能逐漸成熟的背景下，您認為在當前的風景園林教育中應(yīng)該如何開展計算機相關(guān)的教學?

Bradley：我的觀點是，媒體教學需要有它自己的位置，它不能只服務(wù)于設(shè)計工作室。類似于風景園林歷史，我認為數(shù)字技術(shù)在場地建造、生態(tài)、媒體或者其他方面的應(yīng)用都應(yīng)該在課程體系中有它的位置。我知道很多項目都與其工作室聯(lián)系在一起，但我認為目前已經(jīng)能夠確定我們不僅需要了解如何使用這些工具，同時也要學習這些工具是如何產(chǎn)生的以及它們的歷史。關(guān)于教學工具，目前有很多資源，我們可以在Youtube上進行學習。我認為有一點十分重要，就是我們不僅應(yīng)該教授學生如何使用這些工具，更應(yīng)該教給他們一些基本方法來更加有效地利用它們。在每一項訓練中，我們都要求學生運用一個小的工具集對景觀進行概念化的定位。這是通過景觀本身的方式來理解工具的使用方式。不僅僅是如何表現(xiàn)，更是探討它們對于土壤意味著什么？樹木是如何生長的？所有這些方面的教學內(nèi)涵說明我們不僅應(yīng)該教授如何繪制圖案，而且要借助這些工具來探索事物的本質(zhì)。我認為把這2件事結(jié)合起來是非常困難的，但是也是很重要的。

LAJ：因此，媒體應(yīng)該幫助學生理解景觀，理解自然是如何工作的，這都非常重要。

圖片來源：

圖1由耿百利、Jeff Carney、Matthew Seibert繪制；圖2由耿百利、Cheramie、Seibert、Carney繪制；圖3由耿百利拍攝；圖4由哈佛大學設(shè)計研究生院提供。

錄音整理：趙文迪

（編輯/王亞鶯）

LAJ: We know that you majored in computer science as an undergraduate, and then studied landscape architecture at Harvard. Why do you choose landscape architecture?

Bradley:That is a good question. Well, particularly in North America, not many people know about the landscape architecture, until they come across the discipline some how. I studied studio-art and computer science, and then majored in landscape architecture, when I found out about landscape architecture, it was by accident, I didn’t know about it, I like plants, I like the outdoors, but I also like computer graphics. So when I found landscape architecture and all those things come together, it was perfect for me. I found it because I was actually working for a company planting trees and someone told me you can design things with plants, so that is how I found it.

LAJ: I believe that your computer major background has an impact on your researches over the years. You have applied robotic ecosystems or digital modeling more to achieve the autonomy of nature, which is quite different from applying these technology in architectural design and urban planning. So are there any key words or features in your mind regarding the integration of digital technology and landscape architecture?

Bradley:Well, I would like to say there are some key differences between how we deploy technologies in architecture, planning, and even when we look at engineering, most of the disciplines are typically looking for a specific answer. You need to calculate it, you know exactly what it is and then you try to find the most efficient way to come up with that answer, often times, in landscape architecture, and even in environmental design, not only are we using the computation as a way to understand this system’s function but we also have the complexity of human interaction with the environment, and then we have the complexity of biology, other species, and all types of environmental processes or functions, and it is not so easily computable. So, what we see is that we have to develop a new way of using the computer, not only making the models that allow to understand the way nature and the environmental process works, but also allows it to interact directly. So what I believe the biggest differences is that there has to be a way that we work one to one, with the way we create the model, and the way we interact with the environment itself. When we do something to the environment, we get the feedback from that, we allow computing to help us to understand that, and we are able to act on that information, and that doesn’t mean we have to understand everything, but we begin to learn through the power of computation and the interaction of the environment.

LAJ: I have noted that many of your papers talk about artificial intelligence. What do you think is the core challenge of applying artificial intelligence in the current landscape architecture profession? Or what role will artificial intelligence play in dealing with environmental issues?

Bradley:well, there are two parts of these. I mean, well, this is a big question. I think, I could probably talk about this for a few hours. But we just break it up two parts. One is that, our current understanding of the environment essentially depends on two aspects. One, the environment acts in one way, like trees grow certainly and species acts certainly, and we call that nature or even wildness. On the other side of that, we also maintain, construct, create the environment, and often times, we call that landscape, that is, we as human beings intervene to construct it. I think the thing we will see from the forms of AI, particularly, when we are thinking about how to maintain landscapes and the environment, we are going to have another intelligence maintaining landscape and creating a new type of environment that we really never understand, it is highly maintained, but we view it as natural or wild.

So, there is a fundamental change in the way environments are maintained and our relationship with computational intelligence. One thing that we do not quite understand yet, is that not only can we use machine learning to tell us new things about the landscape, but we are also getting to a point where we don’t understand exactly what or how it is accomplishing its procedures. Zihao Zhang and myself have written papers on this idea, that there is actually a third intelligence[1-2]. We have biological intelligence, we are kind of included in that but human beings like to separate themselves, and there is human intelligence, and there is a new computation intelligence, and AI is part of that. Within that there are also three actors, I think, each plays a different role in how we begin to understand, the function of AI on society, as well as in landscape architecture.

LAJ: So you say there is no more about nature, as the third intelligence?

Bradley:It has and will fundamentally change the way you even think about the nature, because we have places and we are already maintaining through complex procedures and they are not left untouched, they are persisting, there are actually lots of procedures intervening there. The intelligence that maintains those kind of changes are not a human intelligence. With that we don’t really understand why a computer does this, because the computational aspects are hidden from us, therefore this creates a new relationship and a novel ecosystem.

LAJ: I have found that from your perspective, you think artificial intelligence should act as a medium in landscape architecture, which is to build a structural system linking people, nature and technology. Could you brief us some of your experiments or practices in the context of this concept?

Bradley:One of way to think about this is in terms of pulling together many elements, as human beings are linking together all these nature and technology, as well as an evolving culture there. We are always trying to find ways of doing that, it is at the heart of what design does. When people take on this effort we favor human beings, so typically, it may perform ecologically but that might be secondary to aesthetics. There is a kind of strange relationship where designers are always favoring humanity, rather than favoring us all the time, it might have other goals, so the result may be we start to have other types of landscapes that are constructed but perform for other species and humans are secondary, once again, highly maintained but productive to other species.

LAJ: What effects do you think artificial intelligence intervention will have on the current process of landscape architecture design?

Bradley:I think I probably said it a lot, so I’m going to say it in a short term. What I’ve been talking about is in a long term horizon, maybe two decades away. But in a short term, I think the biggest change we are seeing is a new way to think about the landscape form and landscape pattern, and that is the most of the way I’ve been using the machine learning and. It is a way of taking very complex system and allowing machine learning to find similarities in those patterns, and start to think about what is in the form and its relationship to other systems, the forms aesthetically may be different, but they all perform the same, and the machine learning helps us with that, because it is not just the form that we see. But it is about what the system performance o, so I think in the short term it will change our perspective from formal inquiry to the performative inquiry.

LAJ: So you mean we should decide what we should design?

Bradley:And design a new technology for it, right? It is not just a form what we see.

LAJ: It is not just a form, it is a strategy or some thing else. The design is a complicated process, which not only includes the scientific logical thinking, but also the perceptual cognition about the site. What do you think is the role of digital technology in the perception of the environment or the artistry of the site?

Bradley:I actually don’t think digital technology changes that much for us, I think in some sense, we are still human beings, we are still using our tools to perform a design in similar way, the major differences are two parts. One is an advantage of digital design, is that of speed, we can make alternatives, we can have choice, much quicker, we can produce very quickly, and the other advantages is that we can develop an analysis that are more precise, and the disadvantage is that we have too much choice, and tangibility starts to disappear, so I think the change is that we have to be acutely aware that we still need some tangible relationship of the site, so the digital makes it more difficult to understand the physical place, so to develop a new way of doing precise site engagement.

LAJ: At last, let’s return to education. Traditional computer technology teaching in landscape architecture education involves more with software learning, such as CAD, Rhino and others. Under the context of rapid development of computer-related technologies and gradual maturity of artificial intelligence, how do you think the computer technology related teaching should be carried out in the current landscape architecture education?

Bradley:So my take is that the teaching of media, it needs it’s own place, it cannot just serve the design studio, so I think similar to the landscape architecture history, in terms of teaching, site construction or ecology, media or other kinds of the computation. They all need their own place in the curriculum. I know many programs tie directly to studio. but I think there is enough discourse now that we not only need to know how to use these tools, but also know where do these tools come from, what is their history. The other part is that teaching of the tools, there are so many resource out there, I mean, we can learn these tools on the Youtube. But I think there is a one thing really important is that we are not only help students to learn these tools, we give them some fundamental ways to use the tools in an effective way. We also immediately ask them to take the small set of these tools and conceptualize the role of landscape in every exercise we give to them. This is a way to understand the tools through the media of landscape. And not only how we represent it, but what it means to soil performance, how trees grow, all of these aspects need to be inherent in the teaching of software, it is not just about making images, it is also about how to use the software to explore the actual physical landscape itself. I think layering these two things together is a really difficult task, but I think layering these two things together is really crucial.

LAJ: So the media should help the student to understand the landscape how does the nature works is very important.

Sources of Figures:

Fig. 1 ? Bradley Cantrell, Jeff Carney, Matthew Seibert; Fig. 2 ? Cheramie, Seibert, Cantrell, Carney; Fig. 3 ? Bradley; Fig. 4 ? Harvard GSD.

Recording collector: ZHAO Wendi