Accessibility, Artificial Intelligence, museums
Staff Researcher
Envisioning the Future of Museum Accessibility ...

With AI’s ability to automatically produce content and process complicated datasets with high accuracy, museums worldwide are exploring ways in which this innovative technology can help them better achieve their missions and advance accessibility efforts. Through case studies, learn about three applications of this technology: content digitalization, language accessibility, and visual description.

Envisioning the Future of Museum Accessibility Through Artificial Intelligence
Artificial Intelligence, Public Policy, News & Announcements
Ian Hawthorne
October News: New Policies and Possibilities ...

October was filled with new debates on AI policies, a halt to one of the most significant AI safety bills in the United States, and a host of new AI developments in video, music, and even podcasts.

October News: New Policies and Possibilities for AI
Data, Fundraising, Marketing
Ian Hawthorne
Data Cultures Part I: The Many Markets of Arts ...

Arts and cultural nonprofits often operate in multiple markets for earned and contributed revenue. With increasing attention on data-driven decision making, effective market orientation often depends on effective data use. This fundamental collection, transmission, use, and interpretation of data within an organization collectively contributes to what can be considered an organization’s data culture.

Data Cultures Part I: The Many Markets of Arts Organizations
Advocacy, Community Building, Public Policy
Ian Hawthorne
Democracy on Display: The Dynamic Role of Art ...

Museums have increasingly begun to volunteer their spaces as polling places, acting as a democratic vehicle for their communities and adding to the greater fabric of America’s election infrastructure. In doing so, they can support local democratic processes and prove to their communities that they are not unbreachable temples for the elite, but open platforms for the people.

Democracy on Display: The Dynamic Role of Art Museums in Elections
Artificial Intelligence, entertainment, Film
Staff Researcher
Part I: A New Era of AI in the Entertainment ...

As exemplified by the Hollywood strikes of 2023, we find ourselves in a new era of Artificial  Intelligence in film and television. While studios are looking to cut costs, performers seek job security, and consumers seek quality content. Through research conducted in collaboration with facial motion capture technology provider Faceware Technologies Inc., Master of Entertainment Industry Management students at Carnegie Mellon sought to gain insight on how AI-generated content will transform existing industries, including how this technology could affect employment in the entertainment industry, content development,  budgets, contracts, legislation, and privacy rights.

Part I: A New Era of AI in the Entertainment Industry

network mapping

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Observing Relationships Between Producers and Fandom through Digital Mapping: Part 3

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Observing Relationships Between Producers and Fandom through Digital Mapping: Part 3

With the emergence of digital fan engagement, fan codes and traits that were once hidden to content makers are now able to be studied on an individual and collective scale through scraping and network mapping. This paper explores how to access information in order to understand fan behavior and the best ways to cultivate fan/producer relationships. While this study focuses on film and television, this information can be used to map digital conversations and communities surrounding all artistic mediums.

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Mapping Movement: Network Mapping in the Dance Industry: Part 2

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Mapping Movement: Network Mapping in the Dance Industry: Part 2

How well do you know the history of your industry? Could you list every branch, every individual, that helped to develop your industry into the complex and beautiful thing it is today? If you asked someone who works in the arts to craft such an image or list, they’d probably be able to give you a significant list of names. Yet, the truth is, a single individual’s list can’t provide the entire picture, just their perception of what the tree looks like.