OpenAI's AI Videos Expose Hidden Bias: A Dark Reality Behind the Code

The Download: OpenAI's Caste Bias Problem and the Dark Side of AI Videos In a world where artificial intelligence (AI) has become an integral part of our lives, it's hard to imagine a time when we didn't have AI-powered chatbots, virtual assistants, or video generators. But behind the scenes, there's a growing concern that these AI models are perpetuating biases and stereotypes, particularly in India, one of OpenAI's largest markets. The Caste Bias Problem In August, OpenAI launched GPT-5, its latest language model, which now powers ChatGPT. While CEO Sam Altman boasted about India being the second-largest market for OpenAI, an investigation by MIT Technology Review revealed that both GPT-5 and Sora, OpenAI's text-to-video generator, exhibit caste bias. This is not just a minor issue; it has serious implications for the way AI models perceive and interact with people from different backgrounds. Caste bias in AI models means that they are more likely to reproduce socioeconomic and occupational stereotypes that render Dalits (formerly known as "untouchables") as dirty, poor, and performing only menial jobs. This is a stark contrast to the reality of contemporary India, where many Dalit people have escaped poverty and become doctors, civil service officers, and scholars. The Making of AI Videos But what exactly goes into creating these AI videos? How do they work, and why are they so prevalent in our social media feeds? AI video generation uses a process called "deep learning," which involves training neural networks on vast amounts of data to learn patterns and relationships. These models can then generate new content based on the patterns they've learned. The process typically involves several steps: 1. Data collection: Gathering large datasets of images, videos, or text that serve as input for the model. 2. Model training: Training the neural network using the collected data to learn patterns and relationships. 3. Video generation: Using the trained model to generate new video content based on the learned patterns. The Dark Side of AI Videos While AI-generated videos have revolutionized the way we consume media, they also come with a dark side. With the rise of deepfakes and AI-generated news footage, it's becoming increasingly difficult to distinguish between what's real and what's not. Moreover, video generation is an energy-intensive process that uses significantly more power than text or image generation. This raises concerns about the environmental impact of AI-powered media creation. Human Interest Elements To understand the implications of caste bias in AI models, we spoke with Dr. Anandhi Sengupta, a social scientist who has studied the intersection of technology and society. "Caste bias is not just a technical issue; it's a reflection of our societal norms and values," she said. "We need to ask ourselves: what kind of world do we want to create with AI? Do we want to perpetuate biases or challenge them?" Multiple Perspectives While OpenAI has acknowledged the issue of caste bias in its models, some experts argue that more needs to be done. "OpenAI's response is a good start, but it's just the beginning," said Dr. Sengupta. "We need to see concrete actions and policies in place to address this issue." Conclusion The rise of AI-generated videos has transformed the way we consume media, but it also raises important questions about bias, stereotypes, and societal norms. As we continue to develop and deploy these models, it's essential that we prioritize mitigating caste bias and other forms of prejudice. In a world where AI is increasingly integrated into our lives, it's time for us to ask: what kind of future do we want to create with technology? One that perpetuates biases or challenges them? The choice is ours. *Based on reporting by Technologyreview.*