SYLLABUS

DM-GY 9103-VISUAL AI STUDIO FOR ART AND TECHNOLOGY

COURSE WEBSITE

The course website is the official source for all dates and assignments. This syllabus provides a general overview and guideline for the course. All dates and assignments may be subject to change at the discretion of the professor.

COURSE GRAD ASSISTANT: Eric He, xh2815@nyu.edu

COURSE DISCORD: tbp

COURSE GOOGLE DRIVE: Visual AI Studio Google Drive

Discord will be our primary communication tool. (Every week you'll post your visual assignments to Discord and to the Class Google Drive)

RESOURCES

STUDENT INSURANCE: *All students are asked to get equipment insurance. This will not only cover the kits IDM sends, but also students' personal belongings. They can get $3000 of coverage for $90 at https://www.collegestudentinsurance.com. An explainer is here: https://github.com/IDMNYU/ER_Insurance.

COURSE DESCRIPTION, OBJECTIVES & STRUCTURE

COURSE DESCRIPTION Co-taught by an artist-technologist and an art historian, this class is a practice-theory hybrid studio for visual AI. Using art historical inspiration, students will make work in a variety of practical modes—from text to image to GANs models and more. Critical writing and exploration exercises will allow students to think about the philosophical and ethical debates surrounding AI alongside their work.

There will be lectures; class visits from machine learning engineers, media theorists, artists and agency heads implementing artificial intelligence in multiple forms; along with hands-on introductions to working with and across AI platforms. There are no prerequisites for this course, students’ own interests will guide a hybrid final project. The course will culminate in an exhibition of students' work at NYU.

IDM PROGRAM LEARNING OBJECTIVES At a graduate (and advanced undergraduate) level, students will:

1. develop conceptual thinking skills to generate ideas and content in order to solve problems or create opportunities. Students will develop a research and studio practice through inquiry and iteration.

2. students will develop technical skills to realize their ideas.

   Students will understand and utilize tools and technology, while adapting to constantly changing technological paradigms by learning how to learn. Students will be able to integrate/interface different technologies within a technological ecosystem.

3. develop critical thinking skills that will allow them to analyze and position their work within cultural, historic, aesthetic, economic, and technological contexts.

4. will gain knowledge of professional practices and organizations by developing their verbal, visual, and written communication for documentation and presentation, exhibition and promotion, networking, and career preparation.

5. students will develop collaboration skills to actively and effectively work in a team or group.

COURSE OBJECTIVES At a graduate level, students will:

1. To explore a range of industry generative AI tools as both artists and technologists, and to consider the philosophical, ethical, and aesthetic contexts for these tools.

2. To learn to both give and receive critiques of artistic and other work produced using generative AI tools. This will culminate in an end of term exhibition for which students will produce their own piece-- with or without AI by choice-- and write their own artists' statements.

3. To demonstrate how existing skills (traditional or digital) can be implemented to work with AI in both hybrid digital-physical and other contexts.

STUDENT LEARNING OBJECTIVES

1. Students communicate their opinions during group discussions and critiques

2. Students learn to read theoretical and journalistic texts critically

3. Students produce thoughtful and finished art projects with or in conversation with generative AI technologies that are intelligent and challenging, and articulate their beliefs in an artist's statement

CONTENT WARNING Our classroom provides an open and safe space for the critical and civil exchange of ideas. Some readings and other content in this course will include topics that some students may find offensive and/or traumatizing. We will aim to forewarn students about any potentially disturbing content, and we ask all students to help to create an atmosphere of mutual respect and sensitivity.

COURSE STRUCTURE This course will include lectures, in class studio work, conversations, demos, readings, viewings, and class visitors.

Presentations and critiques will occur frequently.

Creations, VRLs (viewing, reading or listening) will be assigned on a weekly or bi-weekly basis and may be subject to change.

Critiques Presenting your work in a critique situation is exceptionally useful. You learn to structure your ideas and to articulate them to an audience. Subsequently your audience provides you with constructive criticism that can increase the impact of your project. It is important to take notes when your work is being critiqued. Be receptive to audience responses and remain unbiased. Later you will be asked to reflect upon the feedback you have received. Resist incorporating all suggestions and comments like checking off tasks on a to-do list. Analyze, prioritize, then utilize the feedback that will work for you and your project. So that you have the opportunity to make as much work as possible, we will also have student work for mutual critique on Discord.

Rules of the Critique:

• Be Present and Engaged

• Give Meaningful Feedback to your classmates

  • Avoid vague statements such as “it’s interesting” or “it’s cool” without follow up. Why or how is it interesting or cool?

• Do NOT take feedback personally.

• If possible, employ frameworks and texts from class reading.

POLICIES

GRADING & ATTENDANCE POLICY Your final grade will be based on a synthesis of quantitative & qualitative rubrics:

• Makeup assignments are only available when discussed with and approved by the professor in advance of the due date.

• Each student will be accessed on the commitment, fearlessness, and continuous improvement that their work shows. Incomplete or unsatisfactory work will receive a failing grade.

Quantitative Grading Overview

Qualitative Grading Overview

A. Excellent (90-100: Work of exceptional quality; Exceeds Expectations)

Performance, participation, and attendance of the student has been of the highest level, showing sustained excellence in meeting course responsibilities. Work clearly differentiates itself from other work, has memorable impact, pursues concepts and techniques above and beyond what is discussed in class. The student thoroughly understands the theory and practice behind virtual reality.

B. Very Good / Good (80-89: Work of high quality)

Performance, participation, and attendance of the student has been good, though not of the highest level. Work demonstrates a better than average understanding of virtual reality theory & practice.

C. Satisfactory (70-79: Average; Satisfies course requirements)

Performance and attendance of the student has been adequate, satisfactorily meeting the course requirements. Work is average and competent, showing a basic understanding of virtual reality theory & practice.

D. Poor; Below Average (60-69: Deficient, but passing)

Performance and attendance of the student has been less than adequate. Work is lacking in many or most areas that show any understanding of virtual reality. Problems may include lack of interest, procrastination, poor planning and poor craft.

F. Unacceptable (59 & Below: Failing Course Requirements)

Academic Integrity All work for this class must be your own and specific to this semester. Any work recycled from other classes or from another, non-original source will be rejected with serious implications for the student. Plagiarism, knowingly representing the words or ideas of another as one’s own work in any academic exercise, is unacceptable. Any student who commits plagiarism must re-do the assignment for a grade no higher than a D. In fact, a D is the highest possible course grade for any student who commits plagiarism. Please use the MLA style for citing and documenting source material.

The complete policy on Academic Integrity for Students at NYU can be found at https://www.nyu.edu/about/policies-guidelines-compliance/policies-and-guidelines/academic-integrity-for-students-at-nyu.html

COURSE TECHNOLOGY USE

We will utilize multiple technologies to achieve the course goals. I expect you to use these technologies in ways that enhance the learning experience for all students and are consistent with the NYU Academic Integrity Policy. For all course work, I will explain what technologies are expected to be used and how you can cite their usage. I will also communicate what technologies are not permitted for course work. If you have any questions about the use of a technology for a course assignment/project, please contact me.

AI GENERATIVE TOOLS

You are welcome/expected to use generative AI tools (e.g.ChatGPT,Dall-e,etc.) in this class as doing so aligns with the course learning goal: "Students produce thoughtful and finished art projects with or in conversation with generative AI technologies that are intelligent and challenging, and articulate their beliefs in an artist's statement"

You are responsible for the information submitted based on an AI query (for instance, that it does not violate intellectual property laws, or contain misinformation or unethical content).

You may use AI tools consciously for your final artist statements if this is critical part of the project itself and is framed within the statement and disclosed to both readers and viewers, as well as the reasoning behind using it. However, for your project proposal, individual responses to reading, content, and speakers, on the course Discord, you must write entirely in your own words. This is so we can assess that we are teaching you correctly and that you do or do not understand artistic or theoretical concepts. Part of the purpose of this class is also to hone your own voice as an artist. This is why we want to make sure you’re using these tools deliberately and only when you already have the skillset as a writer to do so with care.

NAMING CONVENTIONS

YearSemester_CourseTitle_NameOfActivity_FirstLastName.fileformat Ex: 24FA_AI_MessingAround_JillianBenizzi.doc

ACADEMIC ACCOMMODATIONS​

If you are student with a disability who is requesting accommodations, please contact New York University’s Moses Center for Students with Disabilities at 212-998-4980 or [email protected] You must be registered with CSD to receive accommodations. Information about the Moses Center can be found at www.nyu.edu/csd. The Moses Center is located at 726 Broadway on the 2nd floor.

RELIGIOUS ACCOMMODATIONS

NYU’s Calendar Policy on Religious Holidays states that members of any religious group may, without penalty, absent themselves from classes when required in compliance with their religious obligations. You must notify me in advance of religious holidays or observances that might coincide with exams, assignments, or class times to schedule mutually acceptable alternatives. Students may also contact religiousaccommodations@nyu.edu for assistance.

DIVERSITY AND INCLUSION

The TCS Department is dedicated to the university's goals for diversity, equity​ and inclusion. NYU is committed to building a culture that respects and embraces diversity, inclusion, and equity, believing that these values – in all their facets – are, as President Andrew Hamilton said, “…not only important to cherish for their own sake, but because they are also vital for advancing knowledge, sparking innovation, and creating sustainable communities. They should be indispensable elements of an NYU education on all of our campuses. A diverse population encounters and appreciates all perspectives of an issue with a wealth of different approaches to confront it. The result is a higher quality of debate, and a more excellent and advanced academic enterprise.”

NYU Global Inclusion and Diversity: NYU’s commitment to building and strengthening a university-wide culture of diversity, inclusion, and equity has led to the creation of the Office of Global Inclusion, Diversity, and Strategic Innovation. As part of the Office of the President, the Office of Global Inclusion provides expert consultation, resources, and innovative strategies to help guide the University—and its uniquely global and diverse student, faculty, staff, administration, and alumni communities—toward a more inclusive future. https://www.nyu.edu/life/global-inclusion-and-diversity.html

TITLE IX

Title IX makes it clear that violence and harassment based on sex and gender are Civil Rights offenses subject to the same kinds of accountability and the same kinds of support applied to offenses against other protected categories such as race, national origin, etc. If you or someone you know has been harassed or assaulted, you can find the appropriate resources here https://www.nyu.edu/about/policies-guidelines-compliance/equal-opportunity/title9.html

OFFICE OF STUDENT LIFE & SERVICES

Office of Student Life & Services (SLS) – formerly the Office of Student Affairs Email: tandonstudentlife@nyu.edu Social Media Handle: @tandonstudentlife Office of Student Advocacy Email: advocacy.tandonstudentlife@nyu.edu Office of Student Leadership & Engagement (OSL&E) – formerly the Office of Student Activities and Resource Center (OSARC) Email: engagement.tandonstudentlife@nyu.edu Social Media Handle: @engagement.tandonstudentlife Tandon Career Hub – formerly Tandon Career Services Email: careers.tandonstudentlife@nyu.edu Social Media Handle: @tandoncareerhub

* If you are experiencing an illness or any other situation that might affect your academic performance in a class, please email Deanna Rayment, Coordinator of Student Advocacy, Compliance and Student Affairs: deanna.rayment@nyu.edu. Deanna can reach out to your instructors on your behalf when warranted.

COURSE SCHEDULE

This is a preliminary schedule. Please see Weeks Schedule for updates and modifications to this course calendar. All dates and assignments may be subject to change at the discretion of the professor.