人工智能服装设计的哲学事理审度

聚智新科技范式、赋能新设计哲学。人工智能应用于艺术设计的技术浪潮引发重“术”轻“学”的现象,需要“技”“道”并行去审度人工智能设计研究应该从哪些论域展开,探其“事”究其“理”。以服装设计为论域媒介,融合哲学、经济、科学与艺术的跨学科研究方法,提出从论域本体及外延认识定位、技术方法定位的哲学高度去求解人工智能服装设计的深度依据。从“事理”内部打开认知人工智能服装设计的哲学规范性研究进路,提出人工智能服装设计研究的本体界定和认识进路。从哲学思考的相关维度解答了人工智能服装设计“是什么、如何是”的问题,提出建构人工智能设计的学理体系进路。为设计师和数据工程师合作开展人机融合设计提供方法论依据,从技术视角解答了人工智能服装设计“怎么是”的哲学问题和技术方法系统进路。     

基于用户心智模型的产品设计

产品设计的目的是最大限度的满足用户需求,在以用户为中心的设计理念下,通过对用户心智模型的研究来理解产品的用户,设计出更适宜用户使用的产品。就用户心智模型的形成与特征进行阐释,分析了用户与设计师、用户与用户之间的心智模型差异,总结出将心智模型应用于产品设计中的理论与方法,旨在有效提升企业产品开发与创新的效度。     

人工智能时代的设计思考

当前人工智能技术对设计研究范畴、设计思维、设计方法和设计表达等产生了巨大的影响,已经成为设计学科的研究热点。为了探讨人工智能带来的设计变革,思考设计师发展的未来,进一步推动人工智能技术与设计行业的融合,构建智能化设计应用体系,首先梳理了人工智能和设计发展的历史,对比研究人工智能与人类智能的关系。然后通过对专家系统、知识图谱、自然语言处理等主要人工智能技术的分析,探索人工智能在设计研究和实践中的应用场景与解决方案。最终发现人工智能技术在设计行业的应用边界正不断拓展,计算机辅助设计正逐渐转向人工智能辅助设计。人工智能技术主要用于辅助设计师的程序性工作方面,虽然降低了专业门槛,但是其无法取代设计师创造力的价值。     

心智模型在产品创新设计中的应用策略研究

目的 探讨心智模型在产品创新设计中一种新的应用策略。方法 以心智模型理论中Indi Young提出的“亲和图”方法为基础,结合现有产品设计案例,对用户任务—行为流程进行深入的分析对比。结果 总结出心智模型在产品创新设计中的4种应用策略,即填补、合并、拆分和变异,并阐述了4种应用策略分别适用于何种类型的产品设计。结论 通过对这4种策略的充分运用,可以帮助设计师更有目的地进行用户研究,给设计师以及企业进行产品创新带来新的思路。     

人工智能产品设计伦理探究

目的 分析当今人工智能产品设计伦理.方法 运用文献法和案例分析方法从设计的伦理出发,分析当代设计中与人工关智能产品的设计伦理问题.从弱人工智能产品和强人工智能产品两个层面来探究产生的影响,从设计师和设计伦理准则以及人工智能产品三者的协同关系做出思考,同时给出相关问题的具体建议.结论 人工智能产品无法替代设计师的全部功能,设计师应该参与人工智能产品设计伦理,设法赋予其对人类友善的动机,使其具备特定的道德品质,做出合乎道德的行为.     

设计中的“身体-意识”

目的 在视觉的、身体的、意识的三个维度上,理解人工物、生活世界与主体意识之间的关系,启发设计师跳出视觉性的窠臼,在更为广阔、深远的哲学和社会科学的语境下,理解设计中的“身体-意识”。方法 以现象学哲学、具身认知科学与意会知识论为基础,通过案例分析,系统阐述设计学中的“身体-意识”概念及其在体验设计中的具体应用。结论 从尺寸的、工程学的、我思的、无身认知的身体进化,到现象的、社会学的、我能的、具身认知的身体是一种认识论的转向,即从笛卡尔的主客二分转向现象学的“身体-意识”与“生活世界”的水乳交融。这样的认识论,也将成为诸多当代设计主题的方法论基础。设计是联结身体与意识、日常生活与物质世界的一个过程,所探索的是人类体验的“可能性”,而不是“必然性”。     

人工智能在设计产业中的应用及发展

目的 对人工智能在设计领域的应用进行梳理与总结,分析当下人工智能对设计流程和设计师的影响,展望未来人工智能对设计行业的影响趋势。方法 使用VOSviewer工具和文献计量法对Web of Science数据库中关于“人工智能在设计领域的创新与应用”的文献进行详细的可视化和聚类分析,深入探讨文献中的核心观点和案例。结果 基于四个主要聚类(AI+技术应用、AI+设计流程、AI+创意协作、AI+影响反思)来展开讨论。特别关注生成式人工智能(AIGC)技术对设计方法和设计流程的影响,指出生成式人工智能在促进设计创新和提升设计效率方面发挥着至关重要的作用。此外,生成式人工智能对设计师的传统角色及设计原创性提出了新的挑战并重新定义需求。预测未来人工智能将进一步整合进设计流程,促进设计创新,更加关注人工智能的原创性、责任边界问题,探讨人工智能与设计师合作的新模式。结论 通过对人工智能在设计领域应用的全面综述,为未来设计创新与人工智能融合提供了有价值的理论参考和发展方向。     

人工智能艺术设计光晕的持续

对人工智能艺术设计光晕的持续条件标准进行分析。以人工智能艺术家的合法身份与艺术设计作品的标准来探讨,发现了人工智能艺术设计具有持续性的“光晕”。人工智能因机械成为“生产主体”并获得了合法的社会身份,成为了文化智能生产中新的“主体”。智能主体所生产的艺术品已经不单是某种原件的原生命力的再现,在狭义的范畴上,其作品是某个艺术家或设计师观念风格的延续,而在广义的范畴上,是人类文明意识的再造,只有远离糟粕、虚伪、丑恶、异化,才能具有如希腊艺术品一样崇高的膜拜价值和形象的魔力。“真”、“善”、“美”依旧是评价人工智能艺术设计作品是否具有“光晕”的标准。由人工智能生产的作品因其机械性地原创了艺术的物质与观念部分,使其具有了“原真性”,而要想通过“善”赋“魂”,则要在数据和伊始的算法设计上构建“善”的设计约规,形成人文关怀和实现阶层的善用。人工智能艺术设计品是人类精神的集体显现,如同折光镜一般,持续折射人类艺术设计理想的“光晕”。     

人工智能背景下设计师能力需求及胜任力模型再建构

目的 随着人工智能技术和设计软件的广泛应用,研究设计师在知识结构和专业能力方面的新需求,并建构人工智能背景下设计师胜任力模型。方法 以文献研究为基础,筛选人工智能背景下设计师胜任力因子,通过专家调研和访谈法获取专家信度,再通过设计师问卷调查和数据分析验证胜任力模型的有效性。结果 设计师除了应具有基本的设计专业技能和设计专业知识以外,还需要具有跨专业整合协调能力,具有跨学科和终生成长的知识结构、人工智能及大数据背景的基础知识,能运用人工智能软件辅助设计信息整理及提高设计流程的能力。同时,更高层次需要设计师能掌握人工智能编程语言,设计数据模型和算法指导机器如何做设计的能力。研究最终分析得出包含4个一级胜任力因子和17个二级胜任力因子的设计师胜任力模型。结论 该胜任力模型的建立明确了设计师在知识、专业能力、创新能力和人工智能技术应用能力方面的新需求,实现了人机能力优缺互补,达到更高效的设计能力水平,同时为高等院校设计人才培养以及设计职业资格评定制度提供了重要的理论支撑。     

负责任的人工智能与设计创新

目的 快速发展的人工智能技术的应用将改变人们在未来的思考和生活方式,重塑社会礼仪和道德伦理,产生巨大而不可估量的影响.数据噪音所带来的潜在社会道德和设计伦理问题可能会对设计创新中的公平性和包容性造成干扰和威胁,潜移默化地加剧社会矛盾,加深社会的不稳定性.因此,在全球化、普适计算和物联网时代,设计需要理性地重新思考其在人文艺术和科学技术之间的桥梁作用,并从新的角度来观察与探究人工智能应用下的"不确定性"问题.方法 面向应用的人工智能的本质是工具性的,然而设计师群体对这种新工具的理解和思辨还有很大的改善空间.设计具备将价值观融入造物的能力和义务,应充分地发挥其特质和作用,借鉴负责任创新中的预期、反思、协商和响应四个责任维度,将责任风险评估、管理和干预全方位地嵌入到人工智能应用设计创新的决策和流程中,以一个包容开放的动态适应机制来应对未来的挑战.结论 设计师是社会创新的重要驱动力之一,需要积极地投身于倡导创新价值、技术及设计伦理的前沿.负责任的人工智能和设计创新应协同制定更具有前瞻性的目标和任务,引领聚光灯照亮人类前进的方向.     

Dark,Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense

Recent progress in deep learning is essentially based on a “big data for small tasks” paradigm, under which massive amounts of data are used to train a classifier for a single narrow task. In this paper, we call for a shift that flips this paradigm upside down. Specifically, we propose a “small data for big tasks” paradigm, wherein a single artificial intelligence (AI) system is challenged to develop “common sense,” enabling it to solve a wide range of tasks with little training data. We illustrate the potential power of this new paradigm by reviewing models of common sense that synthesize recent breakthroughs in both machine and human vision. We identify functionality, physics, intent, causality, and utility (FPICU) as the five core domains of cognitive AI with humanlike common sense. When taken as a unified concept, FPICU is concerned with the questions of “why” and “how,” beyond the dominant “what” and “where” framework for understanding vision. They are invisible in terms of pixels but nevertheless drive the creation, maintenance, and development of visual scenes. We therefore coin them the “dark matter” of vision. Just as our universe cannot be understood by merely studying observable matter, we argue that vision cannot be understood without studying FPICU. We demonstrate the power of this perspective to develop cognitive AI systems with humanlike common sense by showing how to observe and apply FPICU with little training data to solve a wide range of challenging tasks, including tool use, planning, utility inference, and social learning. In summary, we argue that the next generation of AI must embrace “dark” humanlike common sense for solving novel tasks.     

Can artificially intelligent agents really be conscious?

Mind and intelligence are closely related with the consciousness. Indeed, artificial intelligence (AI) is the most promising avenue towards artificial consciousness (AC). However, in literature, consciousness has been considered as the least amenable to being understood or replicated by AI. Further, computational theories of mind (CTMs) render the mind as a computational system and it is treated as a substantial hypothesis within the purview of AI. However, the consciousness, which is a phenomenon of mind, is partially tackled by this theory and it seems that the CTM is not corroborated considerably in this pursuit. Many valuable contributions have been incorporated by the researchers working strenuously in this domain. However, there is still scarcity of globally accepted computational models of consciousness that can be used to design conscious intelligent machines. The contributions of the researchers entail consciousness as a vague, incomplete and human-centred entity. In this paper, attempt has been made to analyse different theoretical and intricate issues pertaining to mind, intelligence and AC. Moreover, this paper discusses different computational models of the consciousness and critically analyses the possibility of generating the machine consciousness as well as identifying the characteristics of conscious machine. Further, different inquisitive questions, e.g., “Is it possible to devise, project and build a conscious machine?”, “Will artificially conscious machines be able to surpass the functioning of artificially intelligent machines?” and “Does consciousness reflect a peculiar way of information processing?” are analysed.     

Artificial intelligence adoption in the physical sciences,natural sciences,life sciences,social sciences and the arts and humanities: A bibliometric analysis of research publications from 1960-2021

Analysing historical patterns of artificial intelligence (AI) adoption can inform decisions about AI capability uplift, but research to date has provided a limited view of AI adoption across different fields of research. In this study we examine worldwide adoption of AI technology within 333 fields of research during 1960–2021. We do this by using bibliometric analysis with 137 million peer-reviewed publications captured in The Lens database. We define AI using a list of 214 phrases developed by expert working groups at the Organisation for Economic Cooperation and Development (OECD). We found that 3.1 million of the 137 million peer-reviewed research publications during the entire period were AI-related, with a surge in AI adoption across practically all research fields (physical science, natural science, life science, social science and the arts and humanities) in recent years. The diffusion of AI beyond computer science was early, rapid and widespread. In 1960 14% of 333 research fields were related to AI (many in computer science), but this increased to cover over half of all research fields by 1972, over 80% by 1986 and over 98% in current times. We note AI has experienced boom-bust cycles historically; the AI “springs” and “winters”. We conclude that the context of the current surge appears different, and that interdisciplinary AI application is likely to be sustained.     

新工艺与人工智能设计的创造心理与社会美学内涵探究

剖析二战结束以来西方兴起的手工艺向纯艺术转化的趋势,揭示手工艺人“由技入道”的定位转换所隐含的理论及现实问题,反思现代主义艺术理念对手工艺的宰制与挪用现象。考察人工智能设计为促进设计与制作再融合所提供的契机,进而提出了新工艺的概念构想。根据具身认知及情境认知理论,分析手工艺创作具有的设计内含于制作,感知与运动协调往复等特征,梳理手工艺的社会美学所彰显的交互、情境、合作等价值,进而论证人工智能设计与手工艺的结合,对于破解身心关系这一创造心理的核心命题,以及由技术具身化对强人工智能可能的路径等方面的理论和应用价值的探索。人工智能在新工艺领域的应用将重启设计与制作的交融,而集研究、设计、制作等职能于一身的新工匠将通过各种实验性探索对“材美工巧”、“心手同体”等传统理念做出创造性的诠释。     

美与“丑”在当代产品设计中的现象与探究

目的反思当代产品设计中存在的美与"丑"现象,并探究其在现有产品设计中的表现形式及未来发展方向。方法以艺术史为基础,在审美艺术随着时代的变化而转变的大背景下,通过对艺术现象收集得出审"丑"在社会发展、文化转型中发生的变化,阐述"丑"在当代产品设计中的表现及应用,并探究未来发展方向。结论审"丑"成为一种新的审美范畴,它是美的另外一种表现形式。艺术家通过"审丑"获得情感上的宣泄和救赎,或批判现实,或寄托情感。重新审视当代中国的审丑现象,寻找美与丑之间的平衡。产品设计中的设计美需要设计师找准产品设计与大众之间、传统文化之间的平衡,理性及清醒的头脑形成自己对"美"与"丑"的认识。     

Conferences 2017

We take a look back at the conferences we attended in 2017. There was a mix between small and large, academic and industry, that gives a broad and exciting view of the patent information usage landscape. The industry conferences have demonstrated, once again, the hot buzz around Industry 4.0 and anything “AI”, while the academic conferences show that there is real progress in the AI direction in computer science, albeit it is rarely used for the intellectual property domain, so far.     

Mines,mountains, and the making of a vertical consciousness in Germany ca. 1800

The insight that scientific theories are “practice-laden” has animated scholarship in the history of science for nearly three decades. This article examines a style of geographical thought that was, I argue, movement-laden. The thought-style in question has been described as a “vertical consciousness that engulfed science in the early nineteenth century,” and is closely associated with the geographical vision of Alexander von Humboldt (1769–1859). Humboldt’s science spanned nature’s horizontal and vertical axes, from Saxon mines to Andean summits, and from the currents of the ocean to those of the aerial ocean. In probing the origins of Humboldt’s vertical thinking, this article opens up a broader history about the industrial practices and travel cultures that originally animated it. Humboldt’s “global physics” first emerged within a context of vertical travel, up mountains and into mines and caverns. Rhythms of the body—lethal for some, “sublime” for others—became rhythms of the mind. A view of nature as set of vertically complementary spaces rippled through mining culture, Romantic art, and the geographical sciences. To trace the earliest routes of Humboldt’s science is to acknowledge the many actors—some celebrated, most unsung—who took part in the making of a vertical consciousness.