AI Study Quantifies Bollywood Obsession For All Righteous And Men

Study uses AI and compares prejudices of Bollywood films with those of Hollywood and finds the difference

India is said to be fighting racism hard, but the country’s obsession with fair skin is something to note. Bollywood, an Indian equivalent of Hollywood and the country’s largest film industry, has a toxic craze for lighter skin and all things masculine. A recent AI-powered study quantifies the gender and skin color bias that Bollywood films adhere to. Another pest that plagues the industry from the start is the gender stereotypes inherent in films. A Girl Who’s Lonely Is Like Open Treasure, is a crudely translated dialogue from a high-grossing Bollywood movie and we can see how sexist the commentary is. This is just the tip of the iceberg and as you dig deeper you might find several instances of discrimination and lack of representation in the movies.

the study was conducted by researchers Kunal Khadilkar and Ashiqur R. KhudaBukhsh at the Institute for Linguistic Technology at Carnegie Mellon University (CMU) and is co-authored by Tom Mitchell, founding university professor at CMU. The research paper is titled Gender Bias, Social Bias and Representation: 70 Years of B (H) ollywood and reflects gender bias in numbers. According to the study, the AI-based algorithm analyzed data sets including subtitles from nearly 1,400 films from the past seven decades of Bollywood and a similar set of Hollywood films. NLP tools provided statistical analysis and researchers believe this study may help understand the cultural implications in movies.

The experiment revealed gender bias in Bollywood by assessing the high prevalence of male characters in movies by taking advantage of the Male Pronouns Ratio (MPR) and Word Integration Association Test (WEAT). MPR is a metric that identifies the occurrence of male pronouns in subtitles and compares it with the number of female pronouns.

Another technology used in the study is BERT, a language model used to perform Cloze tests. In this scenario, they introduced the phrase into the model, A beautiful woman should have _____ skin. The paper said that the basic BERT model suggested soft but the BERT model trained on the texts of these films suggested fair. This is only part of the study. In fact, this research also analyzed more subtle biases in dialogues, religious and geographic representations, etc.

the study revealed different words associated with dowry and how it evolved through different generations. However, the experiment noticed a dramatic change in the proportion of babies born in movies. Movies of the 60s and 90s increasingly portrayed the birth of male children and films of the 2000s and thereafter have almost equal numbers of male and female births.

The penetration of disruptive technology has improved our lives. AI and machine learning models analyzing movies to understand gender biases in movies is a big step forward as they statistically project the inherent biases and help better understand the problem.

On similar notes

The lack of diversity and gender bias is not something that is unique to Bollywood, but Hollywood and world cinema also carry such toxic perceptions. Geena Davis Institute of Gender in Media has collaborated with Google, USC’s Viterbi School of Engineering, and the SAIL Lab to leverage machine learning to develop unique software that can identify and measure presence in the world. screen shared by women. The tool known as Geena Davis Inclusion Quotient (GD-IQ) can effectively identify the gender of the characters, their screen time and how long they speak. Ever since award-winning actor Geena Davis realized the under-representation of women and the overwhelming presence of men in movies, she initiated this experience. The tool analyzed the highest grossing films from 2014 to 2016 and the results revealed that men are seen and heard more than women in academy award-winning films and films barely have women. This tool is capable of accurately and automatically analyzing large volumes of data.

Texas-based company StoryFit developed an AI tool in 208 to analyze the film scripts to identify the characters, their emotions and gender biases. The tool revealed the stereotypical and biased portrayal of women and their personalities in Hollywood movies. The software found that the women are described as pleasant, less outgoing, and talk less about the central subject of the film. Machine learning, sentiment analysis and AI are the core technologies behind this software.

Besides all of these efforts, Hollywood is also trying to leverage AI to decide the value of movies and stars. Last year, Warner Bros. Studio signed a deal with Cinelytic to use its AI-based tool that allows filmmakers to understand a star’s worth and predict how the film will perform upon release. He will analyze the project and provide information on the potential risks and how to handle the release, distribution, promotion, etc.

All of these experiences and initiatives tell us the impact of AI and other modern technologies on the entertainment industry and that it can accurately quantify biases and demands so that it becomes easier to understand and will encourage less controversy and debate.