人工智能时代的设计
Design in the Age of Artificial Intelligence
作者：尼尔·林奇 Neil LEACH
摘要
人工智能在我们的生活中扮演着越来越重要的角色，但它会对设计专业带来何种影响？它会形成一种新的设计风格吗？或者，人工智能仅能辅助设计，还是会颠覆设计？通过定义不同形式的人工智能并展示三位设计师及团队的相关设计成果，本文试图对人工智能的潜力发起讨论。作者认为，人工智能不会创造新的设计风格；但其对设计过程影响深远。这或许将迫使我们反思许多广为设计界所接受的真理信条。某些传统术语（例如，“设计”这一概念以及对于“设计”这一行为的认识）可能会被“搜索”和“结果”等一批新术语所取代。更重要的是，对于“艺术天赋”的迷思可能也会被打破。本文并非意在指出人工智能强烈的“人工性”，而是旨在点明我们对人类智能的理解已深陷误区。
关键词
人工智能；人类智能；功能可见性；搜索；结果；艺术天赋
Abstract
Artificial Intelligence is playing an ever-increasing role in our lives, but what impacts might it have on the design professions? Will it introduce a new style? Or will it just help to improve the design process? Or will it have a completely different impact? This article attempts to offer an overview of the potential of Artificial Intelligence, defining the different forms of Artificial Intelligence, and illustrating its argument with the work of three designers. It argues that Artificial Intelligence will not generate a new style. However, it will have a radical input on the process of designing. It is also likely to force us to call into question many accepted beliefs within the design community. Certain traditional terms, such as the concept of a “design” and the very notion of “designing,” are likely to be replaced by a new lexicon that includes terms such as “searching” and “outcomes.” But, more importantly, the whole myth of the “artistic genius” is likely to be also called into question. What Artificial Intelligence tells us, as the paper concludes, is not how “artificial” Artificial Intelligence is, but rather how misguided our own understanding of human intelligence has been.
Key words
Artificial Intelligence; Human Intelligence; Affordances; Searching; Outcomes; Artistic Genius
基于街道图像与深度学习的城市景观研究
Using Street-Level Images and Deep Learning for Urban Landscape Studies
作者：李小江，蔡洋，卡洛·拉蒂 Xiaojiang LI, Bill Yang CAI, Carlo RATTI
摘要
城市街道不仅是人类活动的集聚地，也是居民与城市建成环境发生社会交互的主要界面。因此，加深对于城市街道景观的了解在城市研究工作中至关重要。街道图像获取性的大大提高为城市景观研究提供了新的机遇，也提高了街道景观研究与分析的准确性与多样性。本研究基于街道图像，呈现了新近研发的深度卷积神经网络在景观分析中的应用。利用经过训练的深度卷积神经网络模型，我们能够准确地从街道图像中识别出不同的城市特征。根据图像分割技术处理结果，我们进一步测算出了马萨诸塞州剑桥市的街道绿化空间分布情况，并对街谷开阔程度进行了量化分析。诸如上述人工智能与大规模采集的街道图像的结合，将为世界范围内的城市景观研究提供全新的视角。
关键词
卷积神经网络；城市街道；人工智能；机器学习；图像分割
Abstract
Streets are a focal point of human activities and a major interface of the social interaction between urban dwellers and urban built environment. A better understanding of the urban landscapes along streets is thus important in urban studies. The increasing availability of street-level images provides new opportunities for urban landscape studies to study and analyze streetscapes at a fine level and from a different perspective. In this study, we presented an application of a recently developed Deep Convolutional Neural Network on landscape analysis based on street-level images. Different urban features were identified from street-level images accurately using a trained Deep Convolutional Neural Network model. Based on the image segmentation results, we further measured the spatial distribution of the street greenery and quantitatively analyzed the openness of street canyons in Cambridge, Massachusetts. The proposed combination of Artificial Intelligence and the massively collected street-level images provides a new sight for urban landscape studies for cities around the world.
Key words
Convolutional Neural Network; Urban Street; Artificial Intelligence; Machine Learning; Image Segmentation
基于智能交互的景观体验增强设计
Application of Intelligent-Interaction-Based Landscape Experience Augmentation
作者：曹静，何汀滢，陈筝 Jing CAO, Tingying HE, Zheng CHEN
摘要
自20世纪90年代中后期起，人工智能和可穿戴交互技术不断革新我们和环境交互的方式，而在未来，这种影响将会愈加深远。可穿戴设备和移动终端主要从感知、理解和控制三个方面增强人对于环境空间的体验。本文围绕智能感官增强、智能认知增强，以及智能反馈增强三个方面，介绍了美国华盛顿纪念碑现场增强音乐项目、由麻省理工学院媒体实验室城市科学研究团队的学者为非专业用户提供智能决策辅助的“城市视景”项目，以及基于地理位置服务的“自然控”自然社区营造实景增强现实游戏应用程序设计等若干创新研究和实践探索，并展望了未来智能交互背景下空间环境规划设计领域可能面临的机遇和挑战。
关键词
智能交互景观；可穿戴设备；体验增强；增强现实
Abstract
Since the mid- to late 1990s, both Artificial Intelligence and wearable interaction techniques have dramatically changed the way how humans interact with the exterior environment, as such influence will be greater and greater over time. Wearable devices and mobile terminals have enhanced humans’ experience on spatial environment by improving their perception, understanding, and ability of control towards certain places. This paper centers on the advanced efforts of the augmentation technologies in intelligent sensing, cognition, and feedback, by introducing several innovative applications, including 1) the live-audio augmented project for the Washington Monument; 2) the CityScope project, developed by the MIT City Science Lab, which provides intelligent decision-making aid for non-professional users; and 3) Nature-X, an augmented reality application that creates nature community scenes based on Location Based Service. All these studied cases of spatial and environmental planning and design look into the future opportunities and challenges in the context of intelligent interaction.
Key words
Intelligent Interactive Landscape; Wearable Device; Experience Augmentation; Augmented Reality
第三类智能
A Third Intelligence
作者：耿百利，张子豪 Bradley CANTRELL, Zihao ZHANG
摘要
将人工智能应用于景观设计学科所面临的首要挑战在于当前人工智能的定义不适用于系统性的景观框架。一般的人工智能定义不关注复杂的生态关系，而是倾向于强调个体智能，忽视了人类和非人类智能体相结合而产生的智能。我们认为，在将人工智能充分应用于景观设计领域之前，针对景观设计学科制定一个切实的“智能”的定义非常必要。我们采用智能体－环境框架来定义景观中的智能，并认为这一定义必须具体而明晰：在探讨智能时，明确智能体、环境和首要目标是十分必要的。从智能的角度来看，设计师通过精心设计分布在环境中的各种智能体来创造景观。而在将人工智能引入景观设计学科的过程中，我们提出了与人类及非人类智能体共同演进的“第三类智能”。而这些智能形式间的相互作用与对话也将为景观设计学科带来新的机遇。
关键词
人工智能；景观设计学；智能体－环境框架；广义智能；第三类智能
Abstract
The fundamental challenge in the application of Artificial Intelligence to the discipline of Landscape Architecture is that current definitions of Artificial Intelligence do not fit within systemic landscape frameworks. Rather than focusing on complex ecological relationships, general definitions of Artificial Intelligence tend to emphasize the intelligence of individual entities and overlook the emergent intelligence of assemblages of human and non-human agents. We argue that it is important to develop a working definition of “intelligence” specific to Landscape Architecture before seriously considering the fruitful use of Artificial Intelligence in the production of environments. We adopt the agent-environment framework for defining intelligence in the context of landscape and assert that the definition has to be specific and situated: when discussing intelligence, it is necessary to clarify the agents, the environments, and the overarching goals. Taking intelligence as a lens, designers choreograph the intelligence distributed among human and non-human agents in the environment to produce landscapes. Introducing Artificial Intelligence to Landscape Architecture proposes a “third intelligence,” co-evolving with human and non-human actors. For Landscape Architecture, opportunity lies in the interactions and dialogues between these forms of intelligence.
Key words
Artificial Intelligence; Landscape Architecture; Agent-Environment Framework; Universal Intelligence; Third Intelligence
人工智能对设计的影响
The Impacts of Artificial Intelligence on Design
作者：刘瑜 Yu LIU
摘要
本次访谈围绕人工智能及其可能的设计应用展开。受访人刘瑜深入浅出地阐述了数据在人工智能领域的作用以及深度学习的边界问题，并就人工智能在现阶段能够发挥的辅助设计功能及其未来发展趋势进行了探讨。刘瑜认为，通过深度学习，人工智能在相对封闭的领域内表现出色，但相比人类充满创造力和伦理性的开放式思维，它仍存在局限，特别是在介于感性和理性之间的设计领域，它无法取代人类设计师进行设计。尽管如此，设计师可以把一些常规的基础性工作交由人工智能去完成，从而在设计创新和用户沟通上投入更多精力。
关键词
人工智能；数据；深度学习；设计；黑箱；白箱
Abstract
This interview centers on Artificial Intelligence and its possible applications in design fields. Yu Liu, the interviewee, explains the role of data in Artificial Intelligence, the boundary for Deep Learning, Artificial Intelligence’s function to aid design, and its future development. Liu also discusses how Artificial Intelligence can work within some particular fields, and the creative and ethical limits of Artificial Intelligence, especially in the design fields, which are between sensibility and rationality. Besides, he explains why Artificial Intelligence cannot take the place of human designers. In spite of this, Artificial Intelligence can be used to do repetitive or routine tasks so that designers can put more focus on design innovation and user experience optimization.
Key words
Artificial Intelligence; Data; Deep Learning; Design; Black Box; White Box
设计视角下人工智能的定义、应用及影响
Definition, Application and Influence of Artificial Intelligence on Design Industries
作者：蔡凌豪，范凌，赖文波，龙瀛，王鹏，辛向阳， Linghao CAI, Ling FAN, Wenbo LAI, Ying LONG, Peng WANG, Xiangyang XIN
摘要
“人工智能”的出现大幅提升了人们的生产及生活效率，但与此同时，人类自身的就业环境也深受影响。那么，对于设计行业而言，人工智能又将带来怎样的挑战与机遇？由此，《景观设计学》邀请了6位来自建筑设计、城市规划、景观设计、工业设计等不同学科的学者、设计师，分别回答了什么是人工智能、人工智能可能对设计师的工作产生何种影响，以及人工智能会创造什么样的生活方式三个问题。多数受访者认为，当前的人工智能并非真正意义上的人工智能，其不具备自我意识，亦无法完成创造性行为。而在参与设计工作时，人工智能虽然可以大幅减少设计师的程序性劳动，但由于其采用的是权重叠加和“去少存多”的数据处理方式，运算结果缺乏伦理性和价值评判，因而还远远无法胜任创造性工作。而在未来，人工智能无疑会对人类的生活方式产生巨大影响，甚至远超出我们的想象。
关键词
人工智能；设计；机器；数据
Abstract
Artificial Intelligence significantly promotes humans’ production efficiency and facilitates our daily life. Meanwhile, the climate of people’s employment is also under great impact. Through a group interview with six scholars and designers from the fields of Architecture, Urban Planning, Landscape Architecture, and Industrial Design, Landscape Architecture Frontiers attempts to provoke public attention on the challenges and opportunities (would be) brought by Artificial Intelligence by asking three questions: What is Artificial Intelligence? How would it influence designers’ working process and final results? And, what lifestyles would we have in the future under the influence of Artificial Intelligence? Most interviewees agree that, though Artificial Intelligence has largely helped us lessen workload on repetitive or routine tasks, nowadays it can neither be intelligent enough to have self-consciousness or perform creative jobs, nor offer ethical solutions or value judgments, because it is operated under weighted computing which is programmed by the majority rule. However, all the interviewees believe that Artificial Intelligence will make a big change on people’s future lifestyles, far beyond our imagination.
Key words
Artificial Intelligence; Design; Machine; Data
机器人自动化建造的景观—自然、运算，以及自动化地形建模中的设计空间
Robotic Landscapes— Nature, Computation, and the Design Space of Autonomous Terrain Modeling
作者：克里斯托弗·吉鲁特，伊尔玛·赫尔克斯肯斯 Christophe GIROT, Ilmar HURKXKENS
摘要
2017年秋，苏黎世联邦理工学院与瑞士国家科研能力中心数字化制造小组就瑞士提契诺州坎顿地区的一条高速公路进行了实验性设计。该项目展示了一系列运用计算机程序和机器人原理研发的设计，基于覆盖整个提契诺河谷的激光雷达点云数据集的景观模型为项目中所有的地形塑造提供了基础。经过历时15周的探索后，项目获得了可喜的成果，同时展现出了一种通过机器人自动化设计来构思景观的新途径。
关键词
机器人自动化建造的景观；自动化地形建模；点云数据集；人类世
Abstract
An experimental studio on a highway site in Canton of Ticino in Switzerland held at the ETH in the fall of 2017 is the result of a collaborative project with the National Center of Competence in Research Digital Fabrication, ETH Zürich. The work shows a series of designs that were developed through procedural and robotic principles. The landscape models based on a Lidar point cloud data set of the entire Ticino Valley served as the basis of all terrain operations. The results obtained after a 15-week studio are encouraging and show the way towards a new way of conceiving landscapes through robotic design.
Key words
Robotic Landscape; Autonomous Terrain Modeling; Point Cloud Data Set; Anthropocene
基于全球性城市中地方社区的数据体验
The Data Experience of Local Neighborhoods in Global Cities
作者：克里斯蒂安·德里克斯，露西·赫尔墨，法比奥·加里西亚，亚历山大·卡奇凯威 Christian DERIX, Lucy HELME, Fabio GALICIA, Alexander KACHKAEV
摘要
本文着重介绍了一款用于评估城市环境状况的搜索引擎平台—CIVITAS。该平台由伍兹贝格建筑设计事务所的SUPERSPACE团队设计和开发，可帮助用户判断某处地域的宜居性或城市体验是否符合其预期或特殊要求。基于空间特征、空间连通性和土地利用密度三类指标，用户可从大量的社会空间数据集中选取所需数据，对整个城市或社区、建筑物甚至具体楼层进行定制化分析。CIVITAS适用于不同的城市，其内部汇编了一套服务于各项城市指标的数据库，并正在将越来越多的全球性城市纳入其中。本文呈现了利用此平台在全球性城市的地方社区中所开展的研究。
关键词
数据；CIVITAS搜索引擎；宜居性；可视化；指标
Abstract
This article introduces CIVITAS, a search engine for urban conditions designed and developed by SUPERSPACE of Woods Bagot to allow stakeholders to identify qualities of liveability and urban experiences that suit their tacit desires and explicit requirements. Large data sets of socio-spatial quantities are selectable to create bespoke analytics across scales from whole city to neighborhoods, buildings, and even floors based on three categories: spatial character, connectivity, and land-use densities. CIVITAS is applicable across cities and a database for urban metrics has been compiled in-house that contains an increasing number of global cities. This article showcases research into neighborhoods within global cities using the platform.
Key words
Data; CIVITAS Search Engine; Liveability; Visualization; Metrics
StreeTalk慢行导航系统
Streetalk: A Navigation System for Pedestrians and Cyclists
作者：刘浏，张帆，周博磊，王舟童，李颖欣 Liu LIU, Fan ZHANG, Bolei ZHOU, Zhoutong WANG, Yingxin LI
摘要
不同于当前以出行效率为主要考量因素的传统导航系统，StreeTalk慢行导航系统更注重行人和骑行者的感受，特别是对安全感和舒适度的需求。通过运用物体检测识别及场景语义分割等技术，城市街景的深度图像特征被提取出来。之后，结合深度学习模型，机器可以预判人类对周边环境的感知，并为数以千万计的街景照片评分，从而建立起可以直观显示街道安全和舒适程度的导航系统。相关技术不仅可以提供定制化、全方位的慢行导航服务，为城市研究及决策、城市景观设计提供相关依据，也为未来城市生活创造了更多可能。
关键词
城市街道；安全感与舒适度；慢行导航系统；深度学习；物体检测识别；场景语义分割
Abstract
Different from the conventional efficiency-driven navigation systems, StreeTalk navigation system is developed for pedestrians and cyclists to optimize their travelling safety and comfort. Through the application of technologies including object detection and scene parsing, the characteristics of urban streetscapes can be extracted. By combining deep learning models, machines can imitate human’s perception and evaluate streetscapes automatically, and intuitively show users the street safety and comfort level of different commuting options. Relevant technologies can not only be applied in offering panorama navigation services for pedestrians and cyclists, but also better support urban research, inform decision-making and urban landscape design, and explore more possibilities for future urban life.
Key words
Urban Street; Safety and Comfort; Navigation System for Pedestrians and Cyclists; Deep Learning; Object Detection; Scene Parsing
基于空间句法模型的数据化城市设计—以吉林市朝阳广场设计为例
The Application of Space Syntax Modeling in Data-Based Urban Design— An Example of Chaoyang Square Renewal in Jilin City
作者：盛强，周晨，凯万·卡里米，路安华，邵敏 Qiang SHENG, Chen ZHOU, Kayvan KARIMI, Anhua LU, Min SHAO
摘要
空间句法是研究城市空间与社会经济活动之间关系的一系列理论与技术，大数据时代便捷的数据获取使得空间句法研究成果能够快速应用于数据分析与设计实践。本文以吉林省吉林市轨道交通站点之一的朝阳广场为例，通过应用线段模型以及视域模型中的多智能体模拟工具，对广场内部及周边街道的交通流量和视域整合度进行了分析，并呈现了将分析结果应用于广场设计及方案评价的全过程，以期提升广场空间的使用率；本文同时展望了机器学习和人工智能等新技术在推进空间句法基础研究和设计应用方面的前景。
关键词
空间句法；数据化设计；多源数据；交通流量；视域整合度；多智能体
Abstract
In the past decades, Space Syntax offers a series of theories and techniques to study the relationship between urban space and social-economic activities, and has been proved effective in analysis and design practices thanks to the open sources in the big data era. Taking the Chaoyang Square Renewal project in Jilin City, Jilin Province as an example, this article introduces the analyses of traffic volumes and visual integration of the square and the connected streets with modeling tools such as Segment Map and the intelligent multi-agent systems in Visibility Graph Analysis. All these analyses provided a basis for the full design process, from conceptual design to proposal evaluation, in order to activate this site through introducing pedestrian vitality. Prospects on new technologies in Artificial Intelligence, such as machine learning, are also explored to promote the research of Space Syntax and related application in urban design.
Key words
Space Syntax; Data-Based Design; Multi-Source Data; Traffic Flow; Visual Integration; Intelligent Multi-Agent System
“多些答复，少些噱头”—致“步道实验室”主持的多伦多更新项目
“More Buzzwords than Answers”— To Sidewalk Labs in Toronto
作者：玛丽亚娜·瓦尔韦德，亚历山大·弗林 Mariana VALVERDE, Alexandra FLYNN
摘要
近来，各大主流媒体和技术相关领域争相报道了美国基础设施公司“步道实验室”将在加拿大首都多伦多建造一座新型高科技社区（即一项名为“步道多伦多”的项目）。总的来说，国际评论界认为，在公众对建造“智慧城市”项目看法不一的情况下，政府将城市规划的诸项决策权下放至一家以数据为主营内容的私营企业的做法，可谓是机遇与风险并存。
与大多数文章笼统谈及智慧城市和技术导向型项目的视角不同，本文旨在以“步道多伦多”项目为具体案例，提出下列5个问题：其一，作为私企的步道实验室（其为互联网巨鳄“谷歌”的姊妹公司）与推进城市水岸振兴的政府公共机构“滨水多伦多”达成合作协议的过程缺乏透明度，且作为推动项目进行的公共合作方，滨水多伦多也未能向市民作出负责任的解释说明；其二，步道实验室对于其将在哪些地块开展更新项目的表述含混不清，使得公众对该私营技术公司并未足够重视多伦多当地规划法规和房地产现状的情况表示担忧；其三，作为一项由数据技术公司积极推进的城市更新规划项目，人们不免怀疑掌控数据信息才是步道实验室的真正意图；其四，这一案例呈现了城市更新项目中合同签订与开发权给予机制的相关问题；最后，正如文中所述，尽管多伦多市议会仍未获知步道实验室与滨水多伦多双方所签订协议的内容，但已经公布的该项目至今为止的推进方式，以及协议签订双方发表的声明，已足以引发公众对于企业和政府责任感的强烈质疑。
关键词
公私合营；专项机构；透明度；担责
Abstract
Many articles have appeared in mainstream media and in tech-oriented venues about Sidewalk Labs’ ideas for a new high-tech neighbourhood in Toronto (a project named Sidewalk Toronto). By and large, international commentary has focused on the opportunities and risks of giving over control over many city planning decisions to a private data-oriented corporation, with people lining up for or against “smart city” ideas, in general.
This article will set aside generalities about “smart cities” and technology, and instead pose a few questions about the particulars of Sidewalk Toronto project. The first question concerns the striking lack of transparency of the agreement between Sidewalk Labs (a Google sister company) and Waterfront Toronto, the public authority promoting the project, which is not directly accountable to the city or the citizens. The second question concerns the equally striking ambiguity about which parcel of land is being sought by Sidewalk Labs — an ambiguity that suggests a worrying lack of concern, on the tech company’s part, about both local planning law and local real estate realities. The third set of concerns is about the ownership of the data that appears to be Sidewalk Labs’ real interest. Fourthly, problems in the contract award and procurement mechanisms will be raised. Finally, even though the agreement has not yet been seen even by city council, the process so far and the statements by both parties raise serious concerns about accountability, the fifth point raised in this article.
Key words
Public-Private Partnerships; Special Purpose Agencies; Transparency; Accountability
设计未来的理想街道
Let Us Design Streets for the Future We Want
作者：安基塔·查克拉，梅琳达·汉森 Ankita CHACHRA, Melinda HANSON
摘要
本文旨在呼吁人们关注街道设计在引入和优先考虑某些用途时的作用，并突显了世界各个城市为将街道从汽车导向转变为居民导向所付出的努力。身处当今时代，我们对于未来街道的畅想被无人驾驶汽车的问世所蒙蔽和限制，却忽视了利用低技术的解决方案有效改善城市环境的可能。本文呼吁人们尽快采取行动以改变当下盛行的街道设计方法，并将衡量项目成功与否的指标由以往的汽车导向型指标转换为强调可达性、安全性、空间公平分配、环境质量、公共健康和整体生活质量的指标。从业者和决策者不应想当然地认为当今城市面临的所有挑战都可以通过技术来解决，而应着重发展那些采纳了优选高效通勤方式且有助于创建市民友好型城市的街道设计。
关键词
街道设计；公平城市；社区参与；公共生活；道路安全
Abstract
This article will call attention to the role of street design in inviting and prioritizing certain uses and highlight efforts made by cities across the globe to move away from car-oriented and toward people-oriented streets. There are many low-technology solutions available to create better cities, and yet, we are in an era where the vision for the future of streets is clouded by the advent of autonomous vehicles. This article will emphasize that urgent action is needed to change the prevailing approach to street design and shift the measure of success away from car-oriented metrics and toward metrics that address access, safety, equitable distribution of space, environmental quality, public health, and overall quality of life. Practitioners and decision-makers should not assume that technology will solve the challenges cities are facing today and should focus first on designing streets that prioritize the most efficient modes of transport and create people-friendly cities.
Key words
Street Design; Equitable Cities; Community Engagement; Public Life; Road Safety
