Computer science is enabling new businesses, new educational approaches, and new forms of cultural expression through enabling new forms of media. But computer science itself, as a discipline, has not traditionally focused on media. In order to continue and expand the remarkable progress of the last two decades of computational media development, computer science must build interdisciplinary bridges with other areas that have greater media expertise, from which new research methods, guiding theories, and evaluation approaches can emerge.
The potential impacts of such connections are great. Combining computer science's model of technical innovation with media knowledge could offer cultural and economic benefits far beyond those that can be attained by the simple borrowing of surface elements more common today. It could enable interactive educational software that builds on structural insights gained from thousands of years of drama. Presentation and discovery software for understanding everything from scientific data to family history could embody composition lessons from the work of great artists and designers. Meaningful new forms of interactive storytelling could build on the experience gained from interpreting literature and cinema. In short, the scientific process of breaking new ground in media technology could have powerful new methods for evaluating research directions and progress that are grounded in our shared cultural heritage.
For enabling such a future, one important interdisciplinary connection is that with arts and design communities, who have developed knowledge in these areas and communities of practitioners already collaborating with computer scientists. Another important connection, which is unfortunately less well established, is that with the humanities. Despite the fact that the humanities have some of the best-developed approaches for understanding media, and despite the emerging digital humanities community with expertise in work with computational systems, the connection between media-focused computer science and the humanities has not yet fully catalyzed. This workshop will be an important step toward building a robust connection, defining the first research questions and collaboration models to be pursued. The potential long-term impacts of these new connections are high, especially in areas where the U.S. has a leadership position and important investments in research and development.
The Media Systems convening, held at UC Santa Cruz in 2012, brought together field-leading participants from media-focused computer science, digital art, and the digital humanities — located in and across universities, industry, federal agencies, publishers, and more. Different participants focused on diverse aspects of how new media forms are impacting culture, education, the economy, and other areas of national importance, using examples ranging from the World Wide Web to computer animation, and from video games to social media. Surprisingly — despite this diversity of background and focus — rather than struggling to explain our different fields to each other, we found ourselves engaged in deep conversation focused on a coherent set of shared activities. In the process of writing the resulting white paper, the authors have chosen to name these activities "computational media" and have identified a number of key elements and recommendations. Computational media involves four types of work, and develops four types of knowledge and skills — generally combining two or more of these categories simultaneously: Technical — computational media work requires and develops deep technical engagement, from the invention of new algorithms to the use of specialized tools for purposes such as 3D animation or examining code archives. Creative — computational media practitioners must exercise creative skills, from the creation of new genres of digital art and scholarship to the imagining and prototyping of new technology and tool possibilities for media. Interpretive — the creation and understanding of computational media requires being able to interpret particular examples and place them in broader contexts, from situating media forms historically to interpreting new kinds of human learning behavior enabled by computational artifacts. Collaborative — computational media work is most often carried out by interdisciplinary teams, exercising and developing 21st Century skills in communication, teamwork, and problem solving. Or, looking at the same activities through a different lens, we could say that computational media work produces four kinds of outcomes (often with outcomes in multiple categories from the same project): Artifacts — the outcome of making novel computationally-driven media. Capabilities — the outcome of developing computational, representational, and design approaches that enable new forms of media. Insights — the outcome of studying the technical, historical, and cultural creation and function of computationally-driven forms of media, both old and new. Practitioners — the outcome of interdisciplinary education and training in computational media. During the discussions at the three-day Media Systems gathering (together with more than a year of followup conversation and writing) we identified a core set of opportunities and challenges facing computational media work. Examining these resulted in the development of 11 recommendations for specific constituencies, which are listed here and discussed in detail in the resulting white paper (soon to be published). In addition, the project also resulted in the publication of online video resources and accompanying essays, graduate student mentorship and training, and deeper connections between organizations involved in this research (with at least one new industry/university collaboration between workshop participants since the workshop). Resulting Recommendations: 1) Support the Creation of New Works and Design Approaches 2) Invest in Developing Computational New Models and Genres 3) Encourage New Forms of Scholarship 4) Cultivate Rigorous Dissemination Venues and Evaluation Approaches 5) Build Interdisciplinary Education and Student Diversity 6) Foster the Next Generation of Leaders 7) Support for Tool and Platform Development 8) Support for Collections and Archives 9) Promote Collaboration 10) Develop Better Field Understanding 11) Establish National Centers of Excellence
