UC Berkeley study uses AI to confirm rising Hollywood diversity

AI-powered study confirms Hollywood’s increasing diversity: Researchers at UC Berkeley have used facial recognition technology to analyze on-screen representation in over 2,300 films, revealing a trend towards greater diversity in Hollywood since 2010.

• The study, published in the Proceedings of the National Academy of Sciences, examined 4,412 hours of footage from both popular and prestige films released between 1980 and 2022.
• Researchers found increased representation for women, Black, Hispanic/Latino, East Asian, and South Asian actors, particularly after 2010.
• The diversity increase is not limited to a few films with all non-white casts but is evident across individual movies as well.

Technological and legal breakthroughs: The study was made possible by recent changes in copyright regulations and advancements in computer vision technology.

• A new federal regulation eased “digital locks” on DVDs, allowing researchers to bypass copyright protections for scholarly purposes.
• The UC Berkeley team had to purchase their own copies of all 2,307 films studied and use secure data handling measures to comply with strict usage rules.
• The university’s Secure Research Data and Compute (SRDC) platform played a crucial role in enabling the research while maintaining data security.

Methodology and findings: The researchers used computer vision to track actors’ appearances on screen but relied on human perception for demographic categorization.

• Actor demographics were determined using Wikidata for gender information and user surveys for perceived race/ethnicity.
• The study found that women’s on-screen presence increased from 25% between 1980-2010 to around 40% in 2022.
• All groups except white men remain underrepresented in leading roles compared to non-leading roles.
• Black actors were found to be underrepresented in award-nominated films compared to popular films, primarily due to disparities from 1980 to 2010.

Implications for future research: The study’s methodology and findings open new avenues for large-scale analysis of representation in film.

• The research team has released non-copyrighted elements of their data to support reproducibility and further studies.
• Future research aims to explore more nuanced questions about representation, including how actors are depicted and potential stereotypes or biases.
• The automated approach allows for analysis of a broader range of films and more detailed questions about representation than previously possible with manual methods.

Broader impact on film studies: This research demonstrates the potential of AI and computer vision in accelerating cultural analytics of film.

• The study complements traditional human viewing methods by enabling large-scale, granular analysis of representation trends.
• Researchers hope to collaborate with movie studios and film scholars to further explore and understand representation in cinema.
• This approach could lead to more comprehensive and data-driven insights into the evolution of diversity in Hollywood and its cultural implications.