Trends & Signals
By: COLLEEN MCCRETTON
Explore the latest insights, thought leadership, and research from FCAT®
Teaching a Robot to Read
August 18, 2021
Over the last several years one of the FCAT AI teams - code named “RoboReader” - has been working on processing documents and taking needed information from unstructured text and transforming it into structured data that can be used by the business. In the course of the work, we have noticed parallels in the way we are “teaching” the system and how we read as humans.
Building Trust in AI Systems
January 28, 2021
Bias in data used by AI algorithms is drawing increasing attention. The internet is full of examples of AI systems bias: recruiting algorithms trained on data that favored male candidates, facial recognition software unable to appropriately identify people of color, medical systems trained with data that is not sufficiently diverse, and many other examples. However, there is another aspect to bias that impacts AI systems and bears some scrutiny as well - the cognitive biases that users bring to the table.