MIND THE DEEP: Artificial Intelligenge & Artistic Creation
脑洞: 人工智能与艺术创造

7 NOV 2019 - 09 FEB 2020

Abstract | Mind the Statement


The exhibition “Mind the Deep: Artificial Intelligence and Artistic Creation” features 28 artworks by 22 artists and artist groups, together with demonstrations from AI conferences, to investigate how artificial intelligence has entered different levels and stages of artistic creation: concept development, logical construction, specific tools, and effects. Further more, the exhibition also elaborates how artificial intelligence associates itself in the concealed brain circuits of our lives nowadays, as well as the collective unconsciousness that is immersed in t

he Technocene. Meanwhile, by featuring tech-demos of artificial intelligence conferences, the exhibition explores how the algorithms can relate to contemporary life in a more straightforward and concrete way.

Introduction | Mind the Curatorial




Almost all of us live in Turing’s land. The functions of storing, addressing, execution, loop, iteration, “if”, “and/or”, as well as errors, are not merely new knowledge and tools brought about by modern computer programs, but also concealed “brain circuits” of contemporary life. They administer our every unconscious switch between mobile apps, catalyse our obsession with process management in daily life, magnify our trust of navigation apps, and guide decisions we seemingly make “without hesitation.” The magnanimity of data mining and the high-performance computing environment have led to unprecedented advances in artificial intelligence, in particular neural networks, which are expanding globally on an industrial scale. The computing system’s tentacles crawl over the whole earth. Yet, this unstoppable technology also brings with it an excess of interactions, uncountable loopholes, ambiguity, errors, and abuse.

According to some researchers, Artificial Intelligence can be roughly categorized into 16 realms, spanning over Machine Learning, Natural Language Processing, Neural Networks, Expert System, Computing Theory and so forth. The denotations of the term “artificial intelligence,” its branches and dominating models, are all evolving with time, yet the technology still finds its way to penetrate into the wider world: today’s world has witnessed the birth of a group of farsighted consumers, and users who are conscious of data and privacy. The definition of “knowledge” has been transformed, as well as the border of “evidence” and “intuition.” “Image” and “text” can fall into the same computable space. Eventually, independent judgement on artificial intelligence will be gradually shaped by each individuals.

If we revisit the early twentieth century, we will notice that no revolutionary concepts stayed in one narrow field. Instead, they evolved into more fundamental legacies shared across many academic disciplines—Werner Heisenberg, Claude Shanon, and Ludwig von Bertalanffy may well have proved this: the mentality of cybernetics and system theory have infiltrated almost every natural and social science fields ranging from computer science, neurophysiology to mass communication; the uncertainty principle even challenged our fundamental understanding of the world. Similarly, “artificial intelligence” never framed itself within computer science: ever since around 2010, artists have noticed how AI has brought to the world a higher level of complexity, chance and bias, and taken a closer look at how AI models has inspired and challenged the preexisting notions of “medium”, methodologies and authorship, forming a new type of critical, speculative framework.  

[1] Becker et al. (2000),Singer et al. (2000), Chen and Van Beek (2001), Hong (2001) and Stone et al. (2001).

Main Purpose and Implementation | Mind the Map

展览一共邀请28件作品,其运用到的技术模型包括对抗式生成网络(Generative Adversial Network),StyleGAN(一种GAN),RaysGAN(一种GAN),自然语言处理(NLP)和各种其他类型的神经网络(Neural Networks),与此同时,作品也维持了包括绘画、雕塑、影像、装置在内的艺术语言。展览也邀请发表于2006年至2019年期间人工智能学术会议技术展示单元的作品,涵盖3维图像生成,基础数学问题解法,海量数据集模式提炼,声音环境侦测与学习等研究。
The exhibition invites 28 artworks which employs a wide range of artificial intelligence models, such as GAN, StyleGAN, RaysGAN, NLP and other neural networks and are manifested via accessible art forms such as paintings, sculptures, moving-images, and installations. The exhibition also features tech-demos selected from AI conferences between 2006 and 2019, encompassing research on 2D to 3D generation, algorithmic solutions to fundamental math questions, pattern recognition from massive data sets, sound detection, and so on.

  • 训练永不止息

  • Relentless Training
    The works in the hall resonate with what’s behind the curtain of the current hype of atificial intelligence: the technological time constructed by Bell Labs and Google. In 1946, point-contact transistor was invented in the Bell Labs and marked the microelectronics revolution which engulfed us into a time of “silicon”. It was also at the Bell Labs that E.A.T was rooted. Two works located in the exhibition hall investigate the intensive data labeling in professional AI industries, and “micro-labor” by normal users, while endow the abstract labor and technology chain with physical embodiment: sixteen workers gather to photograph 100,000 rose petals in former site of Bell Labs, five leporello books chronicle every single captcha encountered by the artists in five years.

  • 导航潜在空间
    人工智能“潜在空间”(Latent Space)是指把高维对象投射到相对低维的空间里,以便表示低维空间中真实数据的变化或概率关系。这个“空间”同时也是基于运算的,二层的作品遍历从AVA到在线3D打印社区在内的各式各样公开数据集,探索着从经典画作,新闻封面到谷歌街景等训练数据所构成的特征空间,创造出商业人工智能算法通常无暇顾及的“不存在的风景”与“被数据侵蚀的日常”,探向均质表面之下实际多极分化的世界图像和技术暗涌。

  • Navigating the Latent Space
    Latent Space in artificial intelligence implies a space where high dimensional objects are projected in lower dimensions to showcase the data patterns or relationships based on probabilities. This “space” is also computational. Artworks on the second floor traverse various open datasets ranging from AVA to online 3D printing communities, and explore the feature space constructed by all sorts of training data: classical paintings, news front-pages, and Google street views, constructing an “invisible landscape” and “data-eroded everydayness” and diving into the technological undercurrents and disintegrated, multi-polarised world image beneath the homogeneity.

  • 创造神与外星人
    Catherine Jones指出科学家们也已经从对生命特征的“局部模拟”而转向“对智慧的主张”。这种膨胀野心的集中体现或许是谷歌的DeepMind。“劳伦”和“人类研究”构建了人与机器的角色反转与镜像。在“火星萨满”,“闭环”,“爱丽丝和鲍勃”,“我们集体意识的守护者”等作品中,智能机器成为我们创造的外星人或者具备神性隐喻的存在,成为今日唯物主义与技术导向的生存观之下新的形而上投射。原本用来执行任务的算法成为了通灵媒介,用来存储数据的“云”也承载了秘密与告解。

  • Building Gods and Aliens
    Catherine Jones pointed out that xxx(original quote). “Lauren” and “Human Study” constructs the interchangeable and mirroring roles between human and machines nowadays. In “nimiia cétiï”,”Closed Loop”, “Alice&Bob”, “Keeper of our collective consciousness” and other works, the intelligent machine becomes aliens we created, a divine metaphor, and new ontological projections within the living attitude guided by materialism and technological submission today. The task-driven algorithms metamorphose into a spirit medium, the “clouds” Originally designed for data storage, now store our secrets and confessions.

  • 人工遗产与美的假设

  • Artificial Legacy and the Hypothesis of Beauty
    Neural networks are capable for “learning”, hereby they learn from “ideal archetypes” accumulated throughout human history: classic sculptures of thousands years, dance imaginaries, theater performances, and faces labeled as “beautiful” on the internet. The result of such training, yet, vibrates between surreal beauty and unsettling, uncanny horror. Machine learning endows us with endless (even effortless) capabilities to produce and synthesize new aesthetic legacies, however, its logic also implies the retreat of diversities and the dominant feature erasing others. It is yet in such artworks that the “impossible”, the “uncommonly seen hypothesis”, are allowed to ponder. 

Demonstration | Mind the Artists and Artworks

Conclusions | Mind the Exhibition

“Mind the Deep”是对DeepMind的倒置。神经网络之”深“(层数)意味着极度复杂,使人“不知其所以然”的运算,而在通用算法领域最顶尖的DeepMind,与”意识”之深或许还相去甚远。如果说DeepMind是现状,那么Mind the Deep则是态度——“深”(Deep)的,百转千回的脑洞,需要关注(Mind),警惕(Mind),和心智(Mind)。
“Mind the Deep” reverses the word “DeepMind.” Depths (layers) of the neural networks imply extreme computing complexities and difficulties of comprehension. Yet the world-leading general algorithms developed by the company DeepMind, are perhaps still far away from “consciousness.” If we think of “DeepMind” as our current millieu, “Mind the Deep” is attitude—the “deep” brain circuits with thousands of twists, desire a “mind,” capable of consciousness, attention, and caution.

Acknowledgements | Mind the Team

策展人: 邱志杰, 龙星如
主办: 明当代美术馆,中央美术学院视觉艺术高精尖中心数据艺术与人工智能实验室
aaajiao,阿尔伯特·巴克-杜兰 + 马里奥·克林格曼 + 马克·马赛尼特,安娜·瑞德尔 + 达莉娅·叶罗勒克,陈抱阳,克里斯蒂安·米欧·洛克莱尔,邓菡彬 + 吴庭丞,道格·罗斯曼,金·高更,杰克·艾维斯,拉比特姐妹,劳伦·麦卡锡,马修·普卢默·费尔南德兹,迈墨·阿克顿,迈墨·阿克顿 + 珍娜·苏特拉,奥斯卡·夏普 + 罗斯·古德温,帕特里克·特雷塞特,邱志杰 + 何晓冬,科斯莫工作室,莎拉·梅约哈斯,西尔维奥·洛卢索 + 塞巴斯蒂安·史梅格,施政,韦恩·麦克格雷格工作室 + 谷歌艺术与文化实验室

CURATORS: Qiu Zhijie, Iris Long
ORGANIZER: Ming Contemporary Art Museum (McaM),CAFA Visual Art Innovation Institute Data Art and Artificial Intelligence Laboratory
CO-ORGANIZER: School of Creativity and Art at ShanghaiTech University
aaajiao, Albert Barqué-Duran + Mario Klingemann+ Marc Marzenit, Anna Ridler + Daria Jelonek, Chen Baoyang, Christian “Mio” Loclair, Deng Hanbin + Wu Tingcheng, Doug Rosman, Gene Kogan, Jake Elwes, LarbitsSisters, Lauren McCarthy, Matthew Plummer Fernandez, Memo Akten, Memo Akten + Jenna Sutela, Oscar Sharp + Ross Goodwin, Patrick Tresset, Qiu Zhijie + He Xiaodong, Qosmo, Sarah Meyohas, Silvio Lorusso + Sebastian Schmieg, Shi Zheng, Studio Wayne McGregor + Google Arts & Culture

References | Mind the Readinglist

  • John von Neumann,The Computer and the Brain, New Haven/London: Yale Univesity Press, 1958

  • Caroline A. Jones,“In Praise of Wetware:Humans must truly understand intelligence to re-create it. ”

  • Hito Steyerl, “A Sea of Data: Apophenia and Pattern (Mis-)Recognition”

  • Fjodor van Veen, “Neural Network Zoo Prequel: Cells and Layers”

  • Adrian Mackenzie, Machine Learners: Archaeology of a Data Practice, MIT Press,2017

  • Matteo Pasquinelli, Alleys of Your Mind: Augmented Intelligence and Its Traumas, Milton Keynes: Meson, 2015

  • Pedro Domingos, Mel Foster: The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World,Basic Books, 2017

  • Ed Finn, What Algorithms Want: Imagination in the Age of Computing, MIT Press,2017

  • Memo Akten, “All Watched Over by Machines of Loving Grace. A digital god for a digital culture.”