Vrushali Sawant is a data scientist with SAS's Data Ethics Practice (DEP), steering the practical implementation of fairness and trustworthy principles into the SAS platform. She leads the marketing initiatives from a responsible innovation perspective for the DEP. With a background in technology consulting, data management, and data visualization, she has been helping customers make data driven decisions for a decade.
As a member of the SAS Data Ethics Practice, I was excited to collaborate with teams at the SAS Hackathon to learn more about their ideas for trustworthy AI. Artificial Intelligence has the potential to make a difference in the real world, and partnering with the hackathon teams was a
AI – just like humans – can carry biases. Unchecked bias can perpetuate power imbalances and marginalize vulnerable communities. Recognizing the potential for bias is one of the first steps toward responsible innovation. Doing so allows users to include diverse needs and perspectives in building inclusive and robust products. Through
In today's world, data-driven systems make significant decisions across industries. While these systems can bring many benefits, they can also foster distrust by obscuring how decisions are made. Therefore, transparency within data driven systems is critical to responsible innovation. Transparency requires clear, explainable communication. Since transparency helps people understand how
Responsible innovation is critical because technology does not exist in a vacuum. It affects us all in unexpected ways. We know analytics has an undeniable impact on society. For example, analytics can help hospitals manage their inventories for essential items like wheelchairs and bladder scanners, help sports teams curate a
