Summary:
- This article discusses when AI and machine learning models may not be helpful for decision-making. It explains that these models work best when the problem is well-defined, the data is high-quality, and the relationships between variables are straightforward.
- However, in complex real-world situations, where there are many factors involved and the relationships are not clear, AI and ML models may not provide reliable or useful insights. The article cautions that these models should be used with care and their limitations should be understood.
- The article suggests that in cases where the problem is not well-defined or the data is messy, it may be better to rely on human expertise and judgment rather than solely on AI/ML models.