In the rapidly evolving field of AI, co-creation transcends conventional workflows and deliverables. It's an approach to develop sophisticated and meaningful interactions between humans and machines. Protected groups require careful consideration to ensure that AI systems are fair and unbiased.
02. Tracing bias
Our interdisciplinary approach is bridges the gap between qualitative and quantitative research. We work with diverse research participants and experts, tracing bias transfer between pre-existing and algorithmic bias. We provide in-depth analysis and visualizations of discrimination patterns.
03. Intersectionality and Detail
We research intersectional perspectives in order to advance fairness metrics for your product. You will gain a comprehensive understanding of potential biases, enabling refined adaptations to dataset compositions and system architectures.
04. Continuous Learning
Based on the evolving AI ecosystem, and shifting societal contexts, we provide continuous feedback and insights to inform your product's design and strategy. We develop realistic user personas for rigorous software testing.
05. Responding to bias
We guide development towards fair and sustainable designs that empower human agency. Our recommendations help align design patterns with ethical standards, and will enable you to build trustworthy AI products.
Our goal is to blend innovation with empowerment, developing adaptive workflows and responsive AI systems that can account for human diversity. We are dedicated to uncovering and addressing bias in order to ensure the fairness and sustainability of AI solutions for all.
Want to learn more?
Let’s discuss how we can help your organization ensure that your AI and machine learning algorithms are fair and AI governance processes are robust.