As AI-powered features (especially generative AI) are rapidly integrated into modern software, testing teams face a critical challenge. Traditional testing approaches focus on correctness and performance but fail to uncover ethical risks such as bias, hallucinations, and accessibility regressions. In real projects, this has led to AI systems that technically “work” yet exclude users, generate misleading outputs, or erode trust. In this talk, Aditi addresses this gap by reframing AI quality as a testable concern and applying practical, tester-led techniques rather than data science-heavy...
Aditi Jain
SDE
Amazon
Aditi Jain is a Software Development Engineer at Amazon in Brand Experience & Excellence, where she builds and test large-scale AI systems used by millions of businesses and customers. Her work spans generative AI, predictive analytics, cloud-native architectures, and accessibility-first design, with a strong focus on reliability, ethics, and inclusive AI at production scale. Aditi has led the delivery of AI-powered customer support systems, generative content platforms, and accessibility compliance solutions aligned with WCAG standards, producing measurable improvements in quality and user trust. Previously, she worked at AMD on AI-driven predictive scaling for high-performance validation platforms and at ISI Research Institute on peer-reviewed AI workflow research.