When adding polynomial terms or interaction effects, what key assumption of regression might be violated?

When adding polynomial terms or interaction effects to a regression model, the assumption of linearity might be violated. The linearity assumption in regression analysis states that the relationship between the independent and dependent variables is linear, i.e., a change in the independent variable will result in a constant change in the dependent variable. When adding polynomial terms or interaction effects, we are essentially modeling a non-linear relationship.