Often machine learning discussions center around algorithms, or features, or datasets--this one centers around interpretation, and ethics.
Suppose you could use a technology like fMRI to see what regions of a person's brain are active when they ask questions. And also suppose that you could run trials where you watch their brain activity while they lie about some minor issue (say, whether the card in their hand is a spade or a club)--could you use machine learning to analyze those images, and use the patterns in them for lie detection? Well you certainly can try, and indeed researchers have done just that.
There are important problems though--the images of brains can be high variance, meaning that for any given person, there might not be a lot of certainty about whether they're lying or not. It's also open to debate whether the training set (in this case, test subjects with playing cards in their hands) really generalize well to the more important cases, like a person accused of a crime.
So while machine learning has yielded some impressive gains in lie detection, it is not a solution to these thornier scientific issues.