Empowering Diversity in Data-Centric AI

Data is king.

At Valence Vibrations, we follow the view of Andrew Ng’s data-centric AI in building robust systems based off a strong data engineering foundation.

Recent backlash about racial bias in Gemini underscores the need for representative diversity in datasets and contextual understanding behind that diversity. Without a comprehensive grasp of the nuances behind diverse datasets, we risk perpetuating biases and inequalities within AI systems.

For the past decade of voice and emotion AI innovation, neurodiversity was not considered an important category of diversity to be represented in datasets, which meant that neurodivergent voices were marginalized by ML models in the same way they are in real-life environments. This exclusion has had profound implications, resulting in exclusionary practices that fail to account for the diverse ways in which individuals experience and express themselves.

We are here to change that.

At Valence Vibrations, we are committed to challenging this status quo. We believe that every voice deserves to be heard, regardless of neurotype or any other characteristic. By actively prioritizing the representation of neurodivergent perspectives in our datasets, we aim to foster inclusivity and create AI systems that truly reflect the rich tapestry of human experience.