Co_Created: The Artist in the Age of Intelligent Machines

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GALLERY GUIDE

ESSAY

We live in a time of rapid and surprising advances in artificial intelligence (AI). Capabilities previously thought impossible for machines have become routine. Artists and writers find themselves contemplating fundamental questions: What is the nature of creativity? What does it mean to be an artist? What is authorship? What is the future of creative practice?

Two years in the making, Co-Created: The Artist in the Age of Intelligent Machines focuses on eight artist-explorers who use machine learning as an artistic medium. Probing the boundaries of learning machines, these artists have been hacking systems, gathering data, training neural networks—all long before the emergence of popular “push the button aesthetic” generative AI tools such as ChatGPT, DALL·E, Midjourney, and Stable Diffusion.

What is the role of the artist? Interpreter? Editor? Instigator? Curator? What role will artists assign to these new technologies? Symbiotic collaborator? Competitor? Inspirational prosthesis? This exhibition and its accompanying programming, which includes a full-day academic symposium and ethics panel discussion, examines these essential questions. We hope to foster the acquisition of basic literacy in the key concepts of machine-learning technology and to encourage an ongoing dialog on the unfolding entanglement between artists and their increasingly capable tools.

Lapo Frati, CyberLoops, 2022 (still)

MINNE ATAIRU’s Igún uses AI to confront the legacy of colonial oppression in sub-Saharan Africa. During their 17-year occupation of the Benin Kingdom (1897-1914), British forces banned the essential ceremonial art of bronze head casting. In an attempt to imagine works lost during this period, Atairu, a Columbia University PhD student, creates photos, films and 3D printed bronze sculptures using AI software trained on images of looted objects in the collections of western art institutions.

LAPO FRATI, a Burlington based, Italian-born PhD student at the University of Vermont (with assistance from IBM researcher emeritus John Cohn) uses neural networks—mathematical models based loosely on the biology of the human brain—to create an interactive art-making environment. Inspired by Norbert Weiner’s 1948 “Cybernetics” theory of human-machine feedback loops, audience members collaborate with a constantly learning AI algorithm in his work Cyberloops. Using hand gestures recognized by camera-based, AI computer vision, they take turns manipulating and crafting an animated sculpture-drawing machine in virtual space.

CASEY REAS is a University of California, Los Angeles professor and influential co-creator of Processing, a programming language for visual artists, as well as founder of Feral File, an online digital art exhibition platform. Reas’ software-based experimental film Earthly Delights 2.2 uses machine-learning algorithms trained on organic scans of raw vegetation. Inspired by the work of 1980s filmmaker Stan Brakhage, the dynamically rendered artwork is in a state of constant flux—endlessly changing speeds and rhythms without a defined duration. Similar to the process-based painters Morris Louis and Jackson Pollock, who opened their work to chance through physical and chemical processes, Reas purposefully relinquishes a degree of control to his software, which independently generates and determines the timing of each of the film’s frames.

JASON ROHRER’s provocative work December Project—presaging OpenAI’s groundbreaking ChatGPT by two years—uses machine learning text generation to help a grieving man converse with his deceased girlfriend. Rohrer is a New Hampshire-based indie game designer whose art practice focuses on the emotional capacity of technology with work included in New York’s Museum of Modern Art permanent collection. In December Project he used Natural Language Generation software, which is capable of creating sophisticated, original written text which is trained on the girlfriend’s social media posts resulting in uncanny and surprisingly moving interactions.

JENN KARSON’s Damaged Leaf Dataset project considers Vermont’s climate-change crisis through the lens of maple and oak leaves damaged by spongy moth outbreaks. The director of the University of Vermont (UVM) FabLab and art department lecturer, Karson, with the help of undergraduate members of her UVM Art + AI Research group, collected, preserved, and documented thousands of damaged leaves collected at her Colchester, Vermont home. Simultaneously playful and cautionary, Karson uses machine-learning tools to metaphorically consume the data set of damaged leaves, revealing underlying patterns in the evocative Rorschach-like shapes. Her machine-learning model then spawns a new generation of leaf forms, which she captures as gem-like engraving on discarded silicon wafers from a Vermont semiconductor manufacturing plant.

MAURO MARTINO is the founder and director of the Visual Artificial Intelligence Lab at IBM Research and is a Professor at Northeastern University, Boston. For the debut of his latest project Mauro Martino’s Exercises in Style, the artist experiments with the emerging technology of text-to-video. A cast of voice actors performs readings of Raymond Queneau’s 1947 book Exercises in Style, which features 99 stylistically different retellings of the same everyday event. Mauro and his team of researchers then use their own custom, generative machine-learning architecture to interpret the text and dynamically create a collection of 99 individual moving image films each with a unique visual and directorial style.

Mauro Martino, Mauro Martino’s Exercises in Style, 2023, BCA Center

JANE ADAMS is a PhD student at Northeastern University’s Data

Visualization Lab, and a MFA alumni of Champlain College, Burlington, Vermont. Adams’ work addresses concerns of “AI transparency”—the difficulty of understanding how self-learning AI technologies arrive at their predictions. Adams’ sculpture Latent Walk Prism visualizes issues of climate change while simultaneously rendering in physical form the highly abstract concept of “latent space” underlying much of today’s AI art animation. Adams also challenges conventional notions of provenance and attribution with a scrolled, 120 foot-long “highly detailed materials list” of the over 17,000 free stock images she used to train her machine-learning work of art.

MEMO AKTEN’S mesmerizing short film All Watched Over By Machines

Of Loving Grace + Deeper Meditations #1-#6 uses American poet Richard Brautigan’s ironic 1967 techno-utopian poem of the same name as source material for software interpreting text into images. Akten, an Assistant Professor of Computational Art and Design at University of California, San Diego, then uses custom software to skillfully exploit flaws in machine-learning, imagegeneration software. The hypnotic result is a psilocybin, fever-dream homage to artists Yves Tanguy, Salvador Dalí, and early 20th century surrealism.

Memo Akten, All Watched Over by Machines of Loving Grace + Deeper Mediatations #1-#6, 2021 (still)

The types of questions raised by the work of the artists in Co-Created: The Artist in the Age of Intelligent Machines are not new. The exhibit’s title is inspired by the landmark 1935 essay The Work of Art in the Age of Mechanical Reproduction by Walter Benjamin. Benjamin examined the notion of authenticity with the advent of a range of the new technologies of mass production—from photography to cinema—used to replicate works of art. Foreshadowing today’s AI dilemma, Benjamin concluded the complex changes were both positive and negative, and ultimately changed the very nature of works of art. Although the technologies undermined the significance and authority of an original work of art, he decided they ultimately opened up the appreciation of artwork to a much broader mass audience.

The work by Co-Created artists is diverse. Karson, Adams, and Atairu have chosen to formally represent their work as tactile sculptural objects, compared to the disembodied, interactive artworks by Rohrer and Frati, or the highly cinematic, moving-image works of Akten, Reas, and Martino. While there are a wide variety of subjects addressed, two themes emerge from the exhibition. Surprisingly, plants and the natural world are at the center of each of Adams, Karson, and Reas’ works—perhaps an understandable reaction to the ephemerality of their technological medium. Atairu and Rohrer, on the other hand each offer unique investigations into the notion of loss and the radical potential for these new technologies to fill the voids left behind.

These artists engage with the technologies of artificial intelligence in their creative practices in different ways. Reas, Adams, Karson, and Atairu might be considered “classic” AI artists, adopting established techniques employed by many machine-learning scientists. They each carefully gather and curate training data, custom-train neural networks, and then use their trained neural networks to create new images that are a unique synthesis of their training data. On the other hand, Frati, Rohrer, Martino, and Akten all deploy custom software for their projects. Akten and Rohrer appropriate commonly available, off-the-shelf, pre-trained AI models—hacking them with custom code to push them in new and unintended directions. Frati and Martino, in contrast, create fundamentally new AI software applications from scratch while integrating existing tools as needed along the way.

Today, intelligent machines meld into our lives in ways that were unimaginable just a decade ago. From recognizing our faces and interacting via speech to mapping travel routes and delivering news to our feeds, machine-learning algorithms are now our constant, disembodied companions. With the recent emergence of generative AI tools such as ChatGPT and DALL-E, the pace of change is only accelerating. The artists of Co-Created: The Artist in the Age of Intelligent Machines are forging new roles and relationships with the transformative collaborative tools of AI and they provide a unique window into the technology-driven changes in store for the future of artistic creative practice.

EXIT EXIT ELEVATOR STAIRWELL TO LOWER LEVEL GALLERY SIDE ENTRANCE CHURCH STREET 1 4 4 3 5 10 6 2 8 9 11 7

1. JANE ADAMS

Pseudocalligraphic Dilletante

Explanations of Statistical Mechanics in Prospecting Arboreal Growth, 2023 reproduction: pen and ink drawing

17 x 24"

2. JANE ADAMS

Latent Walk Prism, 2022

digital print on Mylar and Lucite*

8 x 8 x 3.5"

3. MEMO AKTEN

All Watched Over by Machines of Loving Grace + Deeper Mediatations

#1-#6, 2021

4K video with audio (4:13 m)

dimensions variable

4. MINNE ATAIRU

Igún, 2021

3D printed sculpture

8" x 8" x 12"

digital print on paper (set of three)

10" x 10"

5. LAPO FRATI

CyberLoops, 2022

custom software: interactive generative graphics using audience pose detection AI algorithm

dimensions variable

6. JENN KARSON

Damaged Leaf Dataset

(Generation 1 & 2), 2022

digital print

(2 panels, 406 images each) 90 x 40"

Studio Assistants: Syd Culbert and Giovana Lowry

7. JENN KARSON

Damaged Leaf Dataset

(Generation 3), 2023 etched wafer (set of three)

5" dia.

#OwnYourDataset

8. MAURO MARTINO

Mauro Martino’s Exercises in Style, 2023 video projection with audio (120 m) dimensions variable

9. CASEY REAS

Earthly Delights 2.2, 2019 custom software and video projection, computer* dimensions variable

Courtesy bitforms gallery, New York

10. JASON ROHRER

Project December, 2020

Internet-based custom software, keyboard, computer* dimensions variable

11. OPENAI

DALL·E, 2021

deep learning model artificial intelligence, computer*

All works Courtesy of the Artist Computer hardware courtesy of OnLogic* Price upon Request

KEY TERMS AND CONCEPTS

ARTIFICIAL INTELLIGENCE

A computer program able to perform tasks typically done by humans.

MACHINE-LEARNING

A type of artificial intelligence that does not need to be explicitly programmed and can learn for itself from examples.

NEURAL NETWORK

A common type of machine-learning program loosely inspired by the structure of the human brain which can learn from examples to make predictions.

DATASET

A collection of examples used to train an artificial intelligence program to make predictions.

TRAINING MODEL OR TRAINING ALGORITHM

A set of instructions used to recognize patterns in a dataset to create a machine-learning model.

MACHINE LEARNING MODEL OR ALGORITHM

The end result of a machine-learning training process that is used to make predictions, or even generate original text or unique images.

ARTIFICIAL INTELLIGENCE IS ACTUALLY NOT “INTELLIGENT”

Artificial Intelligence may appear to understand the decisions it is making but in truth it is merely a series of mathematical equations making statistical predictions about the most likely answer based upon its training data.

BIAS AND ETHICAL AI

Artificial intelligence software is ultimately trained and overseen by people—with all of their flaws. Without careful applications of the  principles of ethical AI including explainability, privacy, careful selection of training data and fairness, we risk that our biases will carry over into the systems we create.

PROGRAMS

FAMILY ART SATURDAY

Saturday, February 25, 2023, 11am – 1pm, BCA Center

Get creative and make art together! Families can drop-in at the BCA Center in-person and enjoy an art activity inspired by the visual models, networks, and patterns of AI programs featured in Co-Created.

ETHICAL IMPLICATIONS OF AI

Wednesday, March 29, 6pm, BCA Center

Explore the ethical and social implications of AI in this panel discussion moderatd by Co-Created Guest Curator, Chris Thompson. Panelists include: Randall Harp, Associate Professor of Philosophy, University of Vermont, Burlington; Crystal L’Hote, Associate Professor of Philosophy, St. Michael’s College, Colchester; and Peter Gallo, artist, writer, and art critic.

CREATIVE AI VERMONT SYMPOSIUM

Saturday, April 15, 2023, 9-6pm, Hula Symposium Reception: 6:30-8pm, BCA Center

In conjunction Co-Created, the inaugural Creative AI Vermont Symposium focuses on the unique collaborative nature of AI and artistic practice. Co-Created artists and visiting AI thought-leaders will explore the philosophical, ethical, and cultural ramification of AI and creative practice through a series of talks and student workshops. See BCA’s website to register.

Creative AI Vermont is co-hosted by BCA and the University of Vermont.

GALLERY EXPLORERS: ART AND AI

April 24-28, 2023, 8am-11am, BCA Center

Students will explore and learn how artists and makers create art in collaboration through engaging STEAM-based activities as they create their own art in our BCA Center studio. Ages 9-11 (Limit 10). All materials provided.

Guest Curator: Chris Thompson

Exhibit Coordinator & Director of Exhibitions: Heather Ferrell

Curatorial Assistant: Jacquie O’Brien

Public Programs Assistant: Sarah Jayne Kennelly

Design Director: Ted Olson

AI Graphics: Jane Adams (rendered by Ted Olson)

Co-Created: The Artist in the Age of Intelligent Machines is sponsored in part by the Maslow Family Foundation, Hula, Gravel & Shea PC, University of Vermont, College of Engineering and Mathematical Sciences, and the University of Vermont, Office of the Vice President for Research. Media sponsor, Seven Days.Hospitality sponsors, Lake Champlain Chocolates, Farrell Distributing, and Prophecy Wines. Burlington City Arts is supported in part by The Vermont Arts Council & the National Endowment for the Arts.

135 CHURCH STREET, BURLINGTON, VERMONT, 05401 BURLINGTONCITYARTS.ORG

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