The most advanced ML Observability product in the market
Building an ML platform is nothing like putting together Ikea furniture; obviously, Ikea is way more difficult. However, they both, similarly, include many different parts that help create value when put together. As every organization sets out on a unique path to building its own machine learning platform, taking on the project of building a […]
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We’re excited 😁 to share that Forbes has named Aporia a Next Billion-Dollar Company. This recognition comes on the heels of our recent $25 million Series A funding and is a huge testament that Aporia’s mission and the need for trust in AI are more relevant than ever. We are very proud to be listed […]
If the model already has an initial bias, it could lead to bias degradation over time. This can occur if the data set used to train the model relies on decisions made by the tainted model.
Imagine a “Hiring HR” ML model biased towards male applicants. If the model is discriminatory, fewer female applicants will be hired. Even if there are higher success rates for hired female applicants, after the model processes the input data, there will be fewer samples from the discriminated population, and as a result fewer women will be considered for employment.
Learn more about AI Bias & Fairness here.