Learning from real life Machine Learning failures

What is a real life example of the swiss cheese model relating to Machine Learning? In our 5th meetup, we spoke with the Brasilian ML Engineer Flavio Clesio. In this video, he talks to us about his feelings about when he was working on a recommended system and when it broke without realizing it they ended up recommending the same product to every customer for 18 days straight. He talks about deeper learnings and how it correlates with the swiss cheese model he explained earlier in the talk This is taken from a longer conversation that can be found here: https://youtu.be/9g4deV1uNZo Machine Learning Systems play a huge role in several businesses from the Banking industry to recommender systems in entertainment applications until health domains. The era of "A Data Scientist with a Script in a single machine" is officially over in high stakes ML. We're entering an era of Machine Learning Operations (MLOps) where those critical applications that impact society and businesses need to be aware of aspects like active failures and latent conditions. This talk will discuss risk assessment in ML Systems from the perspective of reliability, safety and especially causal aspects that can lead to the rise of silent risks in said systems. Slides to the talk can be found here: https://docs.google.com/presentation/d/1gP0A_EXLYafeYAak_vM8lA2nwT7EBaNv3QAWkzBC004/edit?usp=sharing Bio: Flavio Clesio is Machine Learning Engineer (NLP, CV, Marketplace RecSys) and at the moment works at MyHammer AG, where he helps build Core Machine Learning applications to exploit revenue opportunities and automation in decision making. Prior to MyHammer, Flavio was a Data Intelligence lead in the mobile industry, and business intelligence analyst in financial markets, specifically in Non-Performing Loans. He holds a master’s degree in computational intelligence applied in financial markets (exotic credit derivatives). This was a virtual fireside chat between Flavio Clesio, Demetrios Brinkmann and