These are the interesting topics...
I'm no hair expert (insert bald jokes here), but from what I've read the Hair Analysis crowd very much frames their work in a similar light as fingerprint examination.
From the documents linked below:
Hair comparisons are a combination of a pattern-recognition process and a step-by-step analysis of a questioned hair and a known sample
Evaluation of shared and distinguishing characteristics is essentially the process used in forensic hair examinations
The microscopic characteristics allow for hair to be categorized into smaller groups
Following their analyses, hair examiners may conclude the following:

The questioned hair exhibits the same microscopic characteristics as the hairs in the known hair sample and, accordingly, is consistent with originating from the source of the known hairs.

The questioned hair is microscopically dissimilar to the hairs found in the known hair sample and, accordingly, cannot be associated to the source of the known hairs.

Similarities and slight differences were observed between the questioned hair and hairs in the known hair sample. Accordingly, no conclusion could be reached as to whether the questioned hair originated from the same source as the known hairs.
Someone please correct me if I'm wrong, but basically you Analyze a hair, visually compare two hairs (One unknown, and one Exemplar) based on progressively smaller levels of detail (classificatory -> specific features) and arrive at an evaluation that includes association, no association, inconclusive. (ACE)
(Sources for statements)
Forensic Hair Comparison: Background Information for Interpretation
Hair Evidence
To their credit, they qualify the strength of their association but their determinations depend on linear analysis, probabilistic assumptions and experience of the examiners. They've admitted this is wrong, but it almost seems as this is where we are headed (linear +probabilistic + Examiner).
The questions I have are:
Is an overstated conclusion an error?
Is an individualization an overstatement?
Would a scale of conclusions (Identification, Strong Association, Weak Association, No Association) (insert your own terms)) create a higher risk of overstating since there are categorically more statements?
Currently, does an 'inconclusive' give the impression of leaning towards individualization and thus represent an overstatement? (we've seen topics where AFIS inconclusives are reported out as leads)
Link to CLPEX thread
Why would we be moving towards a model that is being acknowledged as less than best practice?
Feel free to answer any/all of the questions