“Human” vs. Machine Appraisals

Alex Tajirian

September 06, 2006

Not having the right tool to pound a nail can be frustrating. But, it sure beats pounding it with your head. Similarly, we don’t know the true domain name price-generating model, but we can do a lot with what we have and know.

There are a number of plausible explanations as to why consumers seek “human appraisals.”

Humans like to “control” outcomes. Control can be achieved through human involvement in appraisals. Thus, an appraised value controlled by a human is preferred to a potentially superior one generated by an automated system.
Humans overvalue events that they think they control. Thus, they unjustifiably place more value on a “human appraisal.”
Some customers project from a narrow experience. I constantly hear things like: “I have seen some automated real estate appraisals. They are worthless”; and “I have seen few of these domain name appraisals. They are based on a machine that spits random numbers.”
A human appraisal can potentially be based on an appraiser “randomly picking numbers from a hat.” However, it is very likely that’s not the mental image that customers form of a human appraiser. They imagine due diligence. Thus, the mental image of the process and what an appraiser actually does can be out of whack. Moreover, no matter how many times an appraiser “picks numbers from a hat,” it does not make him a significant appraisal expert.
Human appraisals can have major disadvantages. For example, in a scientific study, Americans were asked which countries were most similar to each other – Ceylon and Nepal or West Germany and East Germany. Most picked the latter. But when asked which countries were most dissimilar, most Americans also picked the same pair. How can a pair of countries be similar and dissimilar? Does this imply that logical analytics is always superior to gut feeling decisions? Not necessarily! However, when it comes to domain names, due to the massive amount of data, analytical models are superior in detecting comparables.

It should be noted that regression-tree models require human tweaking to determine the optimal tree size. Thus, at least in this sense, they are human based.

A similar aversion to automation has been noted in selecting equity investment funds, despite the strong empirical evidence that automated rule-based stock picking systems have outperformed a large number of “human expert” funds.

Hence, one can easily design a powerful statistical test to determine whether or not an appraiser is coming up with voodoo reports. Yet, customers are not demanding such proof!

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