[Bigdaddy]

As I've said before, this is a grad student project. Maybe a team, but surely something that some students at one of our leading universities could tackle in short order. There are two keys, the first of which is to come up with a set of rules to grade the cards. Corner wear, wrinkles, creases, surface wear, centernedness (?), etc. And how do they add up to a grade. People keep saying that the human is required for 'subjectiveness', but isn't that what we want to eliminate? Consistency and a set of codified rules is what I want.

The second is a method to detect alterations - UV light, magnification, edge examination, ink patterns, etc. A couple of different sensors could accomplish this and then train the machine with a good set of unaltered cards (machine learning) and a set of known altered cards so that it can detect alterations. What are the min/max measurements of a factory cut. What should the edges look like? They should be at least as dirty/worn/frayed as the surface.

Both of these techniques could be automated and it would take the human part out of grading. No need to resubmit, looking for a bump. And it would take no more effort to grade a T206 than a 1978 Topps. Cost to grade would not be a function of the cost of the card.

if a company could do this, they could set up a registry for their own cards and include PSA (and SGC, Beckett, etc.) also, but levy a -2 pt bump on any card not graded by them.

This is not rocket science folks. We have carbon dating, we can find criminals through their relative's DNA samples, Facebook knows who is in your pictures before you tag them, cars can drive themselves and you can carry on a conversation with a $35 computer (Alexa). To have people still grading cards is like having a corded, rotary phone in your house. We can do better.