Douglas Rosman

Computer vision allows machines to see and understand their environment. This course will equip students with the practical skills and critical theory needed to both employ and critically engage these techniques. Real-time body tracking, facial recognition and gesture analysis using RGB+D and LiDAR sensors, artificial intelligence and machine learning will be emphasized. Students will explore and critique contemporary applications ranging from automated mass surveillance to interactive installations. A final project will build on in-class workshops, technical exercises, critical readings and discussions.

This studio course investigates the creative possibilities in programming, from


interactivity to information visualization. Students explore interactive


narratives and games, software art, simulations and emergent behaviors, and


other code-based forms. Lectures and demonstrations provide a conceptual,


aesthetic and technical foundation in programming as a creative practice.


Techniques and concepts are presented through the open-source programming


environment Processing, with an introduction to advanced topics such as C++ and


OpenFrameworks.

'Artificial Intelligence' (AI) has infiltrated many corners of our lives. Once used primarily to identify, track, and predict things in the world, AIŒa convenient shorthand for fimachine learningflŒ has now become generativeŠproducing images, language, and anything else that can be parsed as data. Through a hands-on curriculum, students will explore AI tools to create images, video, audio and more, and will approach these AI systems as tools to augment a creative practice, as well as a medium and material in themselves. This course foregrounds experimentation and play as a means to develop a critical understanding of AI and the ethical implications of its use in creative production (and beyond), engaging in discourse around ideas of authenticity, authorship, and labor. Ultimately, students will leave this class with a broad understanding of how AI operates in the world today, and what it means to incorporate this technology into a creative practice.
The course will be technically rigorous, emphasizing a broad exploration of generative AI tools including but not limited to: text-to-image models like Stable Diffusion, text-to-video, Large Language Models, Generative Adversarial Networks (GANs), and generative audio. Although having coding experience will benefit students, this course emphasizes flexibility with technology and software over coding proficiency. Readings and screenings will draw from the work of artists and thinkers like Sofia Crespo, Memo Akten, Mario Klingemann, Hito Steyerl, Trevor Paglen, Joy Buolamwini, Sarah Meyohas, Anna Ridler and Alex Mordvintsev who have been engaging critically with AI since the mid-2010s.
Students will work individually and collaboratively on smaller scale projects early in the semester, producing and sharing works each week. The course will culminate in a larger scale final project and critique. Students will also maintain a 'sketchbook' documenting their experiments and methods throughout the semester.

The goal of this course is to create an active engaged micro-community to support the the successful development and completion of advanced projects. An advanced project is a project that may require special technical skills, hardware, software or other support that may not be available in other ATS courses. An advanced project may be an artistic work or in-depth technical research. Advanced projects will have an measurable or tangible outcome (work of art, publication, software, etc.) and will flow from a formal peer-reviewed advanced project proposal. Students will meet weekly to critically engage each other?s work, participate in discussions informed by the project proposal and share technical skills. Students will meet with the instructor regularly for individual advising, tutorials and discussion as needed to advance the advanced project.

In the wake of the 2008 financial crisis, Bitcoin (and its underlying ¿blockchain¿ technology) emerged quietly as a decentralized alternative to the corrupt centralized banking system. In the decade since, cryptocurrencies have seen widespread adoption, bringing with them ludicrous energy consumption and digital cats worth hundreds of thousands of dollars. But the potential of blockchains¿networked distributed ledgers that keep a tamper-proof record of all transactions that occur on the network¿extends far beyond facilitating digital cash. Will blockchains spawn egalitarian techno-utopias free from authoritarian governments and tech companies? Or is the whole 'crypto' enterprise just a wasteful pyramid scheme?

This course will explore blockchain technology and cryptocurrencies as both a material and context for artistic experimentation, emphasizing both a cultural and technical understanding of blockchains that can inform critical making. As cultural foundation, we will weave a thread through the invention of money, cryptography, the creation of the Internet, the relationship of cryptocurrencies to anarcho-capitalism and libertarianism, posthumanism, surveillance capitalism, planetary-scale computation, environmental impact, techno-solutionism, meme magic, the NFT/¿cryptoart¿ market, and the history of conceptual art. Technically, we will learn the basics of public-key/private-key cryptography, crypto-mining, oracles, and the principles behind Decentralized Autonomous Organizations (DAOs). Practically, we will work primarily with the Ethereum blockchain and the Solidity programming language to create our own tokens (fungible and non-fungible), dApps (decentralized Applications), and smart contracts. We will examine works by crypto/blockchain-adjacent artists such as Simon Denny, Primavera De Filippi, Ai Wei Wei, Eve Sussman, Jonas Lund, Sarah Friend, Bitnik, Larva Labs, Stephanie Rothenberg, Julian Oliver, and Terra0. Additionally, we will look at how blockchain-based platforms are transforming the way both digital and physical art are bought and sold.

Screenings and readings will provide technical and conceptual foundation for blockchain technology. Students will complete weekly homework assignments, as well as midterm and final projects with respective critiques. While some programming experience is encouraged (JavaScript in particular), no coding experience is needed to make meaningful work in this class.

Taken every semester, the Graduate Projects courses allow students to focus in private sessions on the development of their work. Students register for 6 hours of Graduate Project credit in each semester of study.