How does someone become famous on the internet? What does it take to capture our digital attention? While movie stars, rock gods, and other mainstream A-listers struggle to find their place in a sea of emerging technologies and platforms, a new swarm of micro celebrities and influencers has coasted into the cultural space they once filled. Riding a wave of viral content and memes, the newly-famous rule an internet where anyone can have adoring fans… for a price. They are nimble, niche, obnoxious, empowering, and sometimes disturbing. This class explores what happens when fame is freed from the traditional intermediaries of print, television, and radio, when social media provides everyone with the tools to be their own marketing studio and PR department. It examines the transformation of celebrity, from a 19th century sales gimmick to the formidable cultural, social, and technological force it is today. Students will study a wide array of fame-related topics, from the privacy effects of trolling to the class implications of selfies. And we will engage in practices and exercises that produce real-world instances of celebrity in case we, too, wish to join the ranks of the internet famous.
An introductory course designed to provide students with hands-on experience using various technologies including time based media, video production, digital imaging, audio, video and animation. The forms and uses of new communications technologies are explored in a laboratory context of experimentation and discussion. The technologies are examined as tools that can be employed in a variety of situations and experiences. Principles of interpersonal communications, media theory, and human factors are introduced. Weekly assignments, team and independent projects, and project reports are required.
This course will explore the fundamentals of new media scholarship. Together, we will review and engage with different theories of emerging media in its social, cultural, political, and historical contexts. Students will be able to research, think and write critically about some of the central debates in media studies, including new media forms and aesthetics, issues of gender, race, and labor, platforms, infrastructure and various emerging paradigms. Classes consist of theoretical readings, media example discussion, and writing workshops. Prerequisite: WAI (or co-requisite). Fulfillment: IMA Major Foundations/Elective; IMB Major Emerging Media Foundation/Elective.
Re-make: make (something) again or differently. In this class students will investigate why China became the world’s largest importer of waste. They will study local communities in China, how they manage their waste, and explore innovative ways to transform discarded materials or products around us into something new and precious in areas such as art, graphic and industrial design, architecture, fashion, textiles, etc,. Through research and development, students will learn how traditional techniques and new technologies among the sustainable design philosophy can be utilized as powerful tools for addressing social and environmental problems.
Artificial Intelligence Arts is an intermediate class that broadly explores issues in the applications of AI to arts and creativity. This class looks at generative Machine Learning algorithms for creation of new media, arts and design. In addition to covering the technical advances, the class also addresses the ethical concerns ranging from the use of data set, the necessarily of AI generative capacity to our proper attitudes towards AI aesthetics and creativity. Students will apply a practical and conceptual understanding of AI both as technology and artistic medium to their creative practices.
Machine Learning for New Interfaces is an introductory course with the goal of teaching machine learning concepts in an approachable way to students with no prior knowledge. We will explore diverse and experimental methods in Machine Learning such as classification, recognition, movement prediction and image style translation. By the end of the course, students will be able to create their own interfaces or applications for the web. They will be able to apply fundamental concepts of Machine Learning, recognize Machine Learning models in the world and make Machine Learning projects applicable to everyday life. Prerequisite: Creative Coding Lab or equivalent programming experience Fulfillment: IMA/IMB elective.
Since the beginning of civilization people have fantasized about intelligent machines sensing and acting autonomously. In this course we will discover what robots are, learn how to design them, and use simple tools to build them. Students will use open source hardware to explore sensors and electronics, as well as design and build robot bodies and actuators through a variety of digital fabrication technologies. Using a set of community developed tools, students will become familiar with concepts such as mechatronics, inverse kinematics, domotics and machine learning. No previous programming or electronics experience is necessary, however students will be guided through a series of design challenges that their robots should be able to accomplish. With an emphasis on experimentation, peer learning, and teamwork, the objective of this course is to share in the excitement of robotics by enabling students to make their own creations. By the end of the course, students will present a short research paper and documentation about their robotic explorations. Co-requisite or Prerequisite: Interaction Lab or Creative Coding Lab. Fulfillment: CORE ED; IMA Majors Electives; IMB Major Interactive Media Elective.
How can we capture the unpredictable evolutionary and emergent properties of nature in software? How can understanding the mathematical principles behind our physical world help us to create digital worlds? And how can implementing these code-based simulations offer insight and perspective on both environmental and human behaviors. This course attempts to address these questions by focusing on the programming strategies and techniques behind computer simulations of natural systems using p5.js (a JavaScript library in the spirit of Java’s Processing framework). We will explore a variety of forces and behaviors that occur naturally in our physical world. This includes properties of movement, physics, genetics, and neural networks. For each topic, we will write code to simulate those occurrences in a digital environment. The results will usually be visual in nature and manifested in the form of interactive animated coding sketches.
Circuit Breakers! is a course designed to introduce students to the world of hardware hacking and circuit bending for artistic and mainly sonic ends. By literally opening up common battery powered objects such as toys and finding their circuit boards, one can change the behavior of the object by interrupting the flow of electricity, creating novel, unexpected, outcomes. This technique has both predictable and unpredictable outcomes, but it is almost always satisfying. In addition to hacking off-the-shelf toys, students will also build their own circuits with a minimum amount of components. Many of the projects in this course center on common integrated circuits, which students will cajole, trick, and abuse in order to create art.
Today’s technology enables us to collect massive amounts of data, such as images of distant planets, the ups and downs of the economy, and the patterns of our tweets and online behavior. How do we use data to discover new insights about our world? This course introduces ideas and techniques in modern data analysis, including statistical inference, machine learning models, and computer programming. The course is hands-on and data-centric; students will analyze a variety of datasets, including those from the internet and New York City. By the end of the course, students will be able to (1) apply quantitative thinking to data sets; (2) critically evaluate the conclusions of data analyses; and (3) use computing tools to explore, analyze, and visualize data. Throughout the course, we will also examine issues such as data privacy and ethics