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.
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.
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.
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.
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.
The current status of digital programming and investment varies widely across the arts and cultural sector. Some organizations have abandoned the streaming technology they experimented with, while others continue to incorporate digital programs and performances into their offerings. The following research reveals U.S. streaming trends and audience behaviors.
While Spotify has been a frontrunner in the AI field for a decade, its increased infusion of AI into its algorithmic content suggestions has put it into the spotlight with its ‘AI DJ.’ Consumers return again and again to Spotify largely for its enhanced personalization that few other streaming platforms can match. While AI is central to that personalization, it hasn’t surfaced without baggage and some consumer retaliation. It is also worth considering how this technology will further perpetuate algorithmic biases that disproportionately affect Black musicians.
Indie artists have been traditionally excluded from major labels due to their obscurity and improbability of generating revenue, causing difficulty in creating a career. Nowadays, however, independent artists have more power and capacity to survive, even thrive, without the help of a major label. The advent of the internet, streaming, and social media, as well as legislation regulating for rights of independent recording artists, have pivoted the music industry in the 21st century.
Artificial intelligence in the arts is growing increasingly more complex. It is 2022, and robots are co-creating art, NFTs are celebrating and confusing art consumers around the world, and at least 85% of Americans have smartphones that give immediate access to endless amounts of streaming content. However, AI has flaws. This article covers the recommendation algorithms built to support content delivery for this majority, their cultural implications, and bias control.
The entertainment industry in a post-pandemic and streamer-heavy world bears a sigil of secrecy. Viewership data for films and television shows on Netflix, Hulu, Amazon Prime Video, HBO Max, Disney Plus, Apple TV Plus, and other streaming services is highly monitored behind closed doors at these companies. Streaming consumption skyrocketed at the beginning of the COVID-19 pandemic, as people around the world were forced to stay at home. During the same time, online TV/video consumption increased from 1.7 hours to 6.5 hour. The pandemic fast-tracked the world’s shift to streaming, as it became one of the only accessible entertainment platforms, forcing the general public to decide which streaming services to invest in, largely because of cost.
Since the 1980s, it has been industry practice to measure the number of viewers consuming films and television. These measures affect the industry in multiple ways, from advertising sales to cultivating future viewers, and often contribute to the project’s success. As streaming continues to pivot the entertainment industry, other services will begin to release viewership data in a similar fashion. This crucial step in releasing streaming viewership data has the potential to set a new dawn for streaming services: one where data and transparency lead the way into a more informed and impactful industry.
