Your team has built a new robot that roams the halls at your organization and helps with various things such as small deliveries. However, you notice that many employees are opting not to use the robot. When you ask them why they tell you that the robot looks "creepy" and they would rather not interact with it. What's going on here?

You're working on a project and are working with personally identifiable information (PII). What's the best approach to take when it comes to collecting and using this data?  

Your team is working on a new loan decision model that takes a number of factors and data points into consideration and then automatically approves or denies a loan. After a month in operation someone does a review and notices that the system is denying a large number of loans from a certain demographic when all other factors from people in other regions (such as age, salary, and credit score) are the same. What is most likely happening here?  

Your team is running a simulation-based optimization exercise to increase routing efficiency. Learning for this exercise is done through "trial and error". Which type of machine learning approach is being leveraged for this exercise? 

Enhancing and cleaning data is an important action during which phase of CPMAI?