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Comment by jon_richards | Hacker News Reader

Does qualitative data actually exist? Named colors are considered qualitative, but rbg and cmyk are quantitative. Does converting from one to the other switch whether it is qualitative or quantitative?

Surely semantic meaning is qualitative, but look at word replacement in Google search. That’s entirely based on statistics, thesaurus graphs, and other ultimately quantitative data.

The neat thing about neural nets is that they are ultimately making a very, very complicated stepwise function. Brains are not neural nets, but are they doing anything other than create a very complex, entirely numerical, time and state dependent function? No matter which way you try to understand something, ultimately you are relying entirely on statistical inference.

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Kind of does exist even with colors: try to map "brown" into an RGB or CMYK data point.

I think the real difference is that in qualitative data the numerical representation does not mean anything. Sure, the names of the archangels can be represented digitally (quantitative) but that is just a change of representation - the bit strings' numerical value carries no theological meaning.

Brown is (165,42,42). You can argue about false precision, but the term “brown” has false precision as well. The likely variation in interpretations can be described by error bars. Your understanding of someone saying “brown” is informed entirely by statistical inference of your past experience with “brown”.

Changing the representation of the names doesn’t matter, but attempting to understand the meaning behind the names is ultimately quantitative. The numbers are run in the giant black box that is your brain and then your consciousness receives other qualitative answers.

Asking for an AI without statistical inference or quantitative data is asking for consciousness without a brain.

What is quantitative in understanding the meaning of a name? We don't know that the brain runs on "numbers" (and no, it's no just like a "computer").

To respond to your edit: That is not brown... there is a whole science of color perception, have a look.

It’s not a computer, but it is quantified.

That touches on the really tricky point that some things can be quantified but not computed, so again, we don't know how that measurable representation relates to they way results are derived.

Numbers implies you can do mathematical operations on them that makes sense.

So how would you quantify "good" or "bad"? You can't unless you also answer what "good" + "bad" should be. In psychology they just assume that mapping those onto 1 and 5 makes sense, so "good" + "bad" = 5 + 1 = 6, but that doesn't make sense since it would imply that "good" is the same as "bad" + "bad" + "bad" + "bad" + "bad". You get similar but different issues if you start including negative numbers, or if you just use relative measures and don't have a proper zero, no matter what you do numbers doesn't properly represent feelings as we know them.

It is quantitative, but in an abstract way.

You see the color "brown" as a reception of a photon of a certain wavelength onto your retina, which is sent to your brain.

Visual perception can be equated to camera perception, but the data isn't represented the same way. Humans are just much better at "analog input" than computers are.

When you see things around you, it's natural to try to classify it at multiple levels. In our early formative years, we learn shapes, lines, colours, etc.

This said, "Brown" is just a label we put on a the perception of a photo's wavelength, which is quantitative on the light spectrum. All raw data is quantitative. Qualitative data are just the labels we put on it, but if we're going to general intelligence, we can't shortcut learning this way.

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