Detecting Ethnicity in Videos and Improving Ethnicity Awareness Through Computer Vision

Background

The need for improved ethnicity awareness in media is growing, as biased portrayals of ethnic groups persist in broadcast content. Omdena collaborated with Ceretai to develop the Ethnicity Detection project, which uses advanced machine learning (ML) algorithms to classify ethnicities of individuals in TV broadcasts and videos. The goal is to foster awareness and understanding by employing artificial intelligence to detect faces and classify ethnicities, ultimately promoting inclusivity and combating discrimination.

Objective

The main goal of the Ethnicity Detection project was to create an AI-powered solution that could automatically identify the ethnicity of individuals in TV broadcasts and videos, alongside detecting faces. By employing machine learning, the project aimed to reduce bias in media representation and enhance ethnicity awareness in visual content.

Approach

To tackle the problem, Omdena and Ceretai used active learning techniques to refine the classification model for the Ethnicity Detection project. This approach included a combination of uncertainty sampling and diversity sampling to label the most informative data points, ensuring a balanced representation of ethnic groups. The model was trained using a large set of images and videos, incorporating a human-in-the-loop strategy to mitigate labeling errors and enhance accuracy. Various validation methods were employed to prevent overfitting and ensure the model could generalize well across diverse datasets.

Results and Impact

The Ethnicity Detection project successfully developed a classification model that accurately detects faces and classifies ethnic groups in video content. This tool has significant implications for improving media representation by providing automated analysis that can highlight and reduce ethnic biases. The broader impact includes promoting diversity in media content and fostering a more inclusive environment for audiences. By leveraging machine learning, the solution helps media companies and content creators evaluate their representation strategies effectively.

Future Implications

The outcomes of the Ethnicity Detection project could pave the way for future research in enhancing ethnicity awareness in various fields, including entertainment, news, and advertising. It also raises important discussions about the ethical use of AI in monitoring and ensuring fair representation. As technology continues to evolve, such models may be adapted to identify and reduce biases not only in media but also in other sectors like hiring practices and public policy.