The error for each trait is defined as the difference between the value predicted by the algorithm and that of a standard measurement test (such as NEO-PI-R).

Example: if the algorithm predicts 10-40-60-40-80 for the OCEAN traits of a person, and the last standard test gave values of 50-50-50-50-50, the total point difference would be of 100, and the average error of 20 points would lie within the acceptable range.

The scale over which the traits are measured is not central to this question: on a 5-point scale, the allowed averaged error would be of 1 point or less.

The question also resolves positively if different algorithms can be used to predict individual traits with enough accuracy such that a simple ensemble system using these algorithms and the same naturalistic input would reach the threshold specified above.