Limitations and Mitigations

In addition to superior performance and some other appealing features, those DNN -assisted methods also have some potential limitations. In this chapter, we discuss some concerns, such as observed data being different from training data, improperly chosen input variables for DNNs , etc. We further focus on several mitigation approaches. Such a discussion reflects a key point in Chapter 1 that human intelligence is important to ensure that those AI -based methods perform properly or are able to achieve certain bottom-line properties even under some unexpected scenarios. We strongly recommend a well-designed framework to safeguard AI -based methods based on statistical or scientific expertise.