@ James - As you say: Be careful of what you ask for.
That is a good analogy - it caught me off guard initially but I can see it now.
Hardware - > Instinct
Firmware - > Mood
Software - > Emotion
That is a pretty good “one for one” analogy James.
Very good question - I should have known I would not have got that one past you.
A short answer to your question: pattern matching.
Now for a much longer answer:
Take into account that what I am about to write is straight off the top of my head and I try to make a habit of not memorizing too much so if there are any discrepancies I would like to apologize in advance - you are welcome to request for me to clear those up if they appear.
Now regarding measurement - I can tell you that it is only early days, especially with instinct, mood and emotion - but I have an idea that the best place to start would be at the level of society, much like you do in some of your examples.
I do not want to alarm anyone here - I can say that some pattern analysis already takes place - it seems unavoidable in a world full of fear. Current techniques are a little shortsighted but that is my opinion.
There would be a typical baseline developed over time among any activities that develop patterns - this would be apparent among your SAM Coops or similar structures but it is even easier with the current structure of global society.
To name a few activities in global society that develop patterns:
schooling - logistics - crime-rate - days off from work - crop yields - network patterns associated with news reports - weather patterns - sickness rates - mental health data - war - traffic data and much more.
These activities could then be placed into an ontology of activities along with their baseline and their interactive elements. This ontology would be used to define and help manage the analysis of interactions between the above activities using a pattern recognition engine to check for deviations from their baseline. The ontology becomes the pattern buffer so to speak. The ontology lives inside a “living data base” whereby the database can change “on the fly” using subtle deviations over time to update within specified limits. The pattern recognition engine is able to build the ontology to begin with. When anomalies are detected an alarm can be set off.
If it is something that can develop a pattern then it is able to be studied without invading privacy or corrupting any other ethical concern. It is alarming what is already happening and I would prefer this sort of thing to be known - it would be better for society if society is aware of the things that go on in the data centers, behind closed doors or how ever else you want to apply a term for it. Eventually privacy will be the least of our concerns if we don’t awaken to the mess developing right now.
This is not to say that all of this data is needed - generally crime rates are a good red flag. Once a red flag is detected then a secondary process can be put into place. If logistical operations are affected it could be due to weather or sickness among employees - first you would rule out weather and if weather is not a factor you could move on to sickness - sickness could be false data in which case if a flag is raised then employees could be requested to have a meeting that a psychologist is present at. Falling grades at school is another red flag for many things: domestic problems, death in the family, bullying, dietary habits et cetera - incidentally school grades and crime rates work well together.
Sifting out information at the level of an individual is a little more difficult - psychology only has so many tricks up its sleeve - biological monitoring is useful - there will be new methods that will be spurred on by the neurosciences - the thing to watch here is: invasion of privacy and other ethical concerns - but where there are patterns there are metrics.
Instincts have patterns associated with them as do moods and emotions - it is just a matter of determining these patterns and the metrics follow. Over time human and animal behavior develops typical patterns. Orbits in star systems have patterns. If it is moving it is likely to develop a pattern. The evolution of a pattern tends toward convergence too which is why we see some overlap in the sciences with similar mathematics being applied to more than one science. Even chaos systems have some form of pattern that develop - it is hard to say whether chaos even exists at the human level because that would infer complete disorder and confusion which even in this world of crazy people doesn’t really show itself.
Warning: Tech Talk
The type of pattern matching techniques I have come across are scarily simple and extremely effective - forget Artificial Neural Networks(ANN) and Convolutional Neural Networks(CNN) - they are slow, complicated and ineffective compared to the tech I have come across. It turns out to be easier than we once thought and soon a revolution is about to begin. Add that to the worlds social demise and guess what? People need to take notice now because ignorance will no longer be bliss and obviously rioting, protesting, boycotting and not supporting these things will not achieve a damn thing; that is for the sixties and things have seriously changed since then.
I like to consider the story of the perceptron, to give people an idea of how long these things have been around; “The perceptron algorithm was invented in 1957 at the Cornell Aeronautical Laboratory by Frank Rosenblatt”. They are essentially still with us in a more complex form of the previously mentioned ANN’s and CNN’s. It turns out this year would be the sixtieth anniversary of the perceptrons inception.
Logic seems to be the easiest to measure mainly because logic has many defined patterns associated with it. But inevitably emotions have patterns like moods, they are just at a lower resolution. Anyhow we have mapped a significant portion of the neocortex which is probably the most powerful part of the brain, so many derivations of neocortex patterns can be traced back to emotion, mood and instinct; to the limbic system and reptilian complex respectively. The columns and layers in the neocortex are easily transposed onto computer memory and GPU’s and CPU’s can do the rest of the work. Once you add FPGA’s to the picture things speed up drastically. Human memory is arranged in such a way as to be a hierarchy that uses time based patterns. You can imagine how easy that is to map onto software and hardware.
End of Tech Talk
That is just one technique I can think of off the top of my head. I have learned to detect patterns myself - with my own mind on a conscious level - a computer is of course better at it but people can be taught to do it. In fact most people automatically do it to more or lesser a degree.
There is more to the answer than that but I think I have gone on for long enough. Also take into account that this is a singular proposal out of potentially many more. There is always more than one way of doing something - all I have to do now is put it in a more summarized format.