How AI and Algorithms Can Fail to Detect Anomalies or Fraud

Underrepresentation – A Challenge in Recognizing Anomalies or the Christmas Tree Case

Blog Entry EP-KI-Blog /

Who hasn't experienced this: AI-supported systems suggest a wide variety of products, even though we have only looked at them once. This may be annoying or even irritating, but it becomes much more important when systems are supposed to detect potential fraud or errors. Then we need to be able to rely on them to behave as we intend. Unfortunately, the world of data is rarely uniform, but very diverse. In our new blog post, we share with you what we need to watch out for when developing algorithms that are underrepresented.