Month: June 2019
Information streams plus interpersonal communication are the foundations of philosophical psychology
In this context, an information stream is a stream of information that largely fills the minds of all who are in it such that they know much more about that information than any other.
They value that stream and believe it or believe in it more than any other stream. All human cognition and psychology is taken from and conditioned by primary information streams.
Information streams are essentially “religions.” They include all of the world’s religions in addition to other fundamental belief systems such as science, politics, atheism, a life of crime, and so on.
Interpersonal communication is the most intimate or subjectively honest communication an individual human engages in.
The quality of our subjective honesty defines human life on planet earth, especially conscious human life.
The following follows:
- it is impossible for any individual human to know more than a few information streams well
- very few, if any, humans have really good interpersonal communication; very few are deeply, effectively, and richly subjectively honest with anyone else
- thus, virtually all humans are trapped within the confines of their information streams (“religions”) and their unrequited personal subjectivity
- and thus as a substitute, we fight or feel sad or become narcissistic or seek reclusion or take drugs or pursue money and power or sports and so on
I would maintain that once you see the above trap we humans are in, if you are of sound mind, you will want to escape.
We can never fully escape our need for some information stream (we have to have something) but we can escape to some extent by knowing that there are many information streams and none of them (as far as we know) can claim perfect information.
And, though we can never fully escape subjective isolation, we can escape to some extent by doing FIML practice.
The best way to view information streams is learn about a good many of them and then assign probabilities to how true they seem to you.
For example, I might hold that a materialist explanation of the cosmos has a 10-15% chance of being completely correct and a 25% chance of being a valid part of a larger whole that is more correct but has not yet been determined or discovered.
Assigning percentages mainly helps the mind categorize and assign resources. This, in turn, affects what we read, talk about, and do.
In addition to the percentages provided above, I might assign another 25% to the Buddhadharma and another 25% to the Buddhadharma plus all of the other world religions. Then I might assign 15% to the invented God argument and then some to the simulation argument and so on.
You can do this in any way that suits you. Your percentages don’t have to add up to one hundred, but it is good to have at least a rough calculus to provide some order to the many streams of information available to us.
My own percentages go up and down. The largest one is I cannot honestly be sure of very much but believe it is profoundly worth trying to be more sure or better at trying.
I believe the above description plus having some dedication to an endeavor sort of like that is a good definition of philosophical psychology.
To my eye, philosophical psychology is a good information stream to be in because it stresses how we think and what we think about while also paying full attention to our humanity.
Machine learning used to successfully predict psychosis
A very interesting study shows that a computer analysis of language use has predicted early signs of future psychosis with ~90% accuracy in at-risk individuals.
,,,results revealed that conversion to psychosis is signaled by low semantic density and talk about voices and sounds. When combined, these two variables were able to predict the conversion with 93% accuracy in the training and 90% accuracy in the holdout datasets. The results point to a larger project in which automated analyses of language are used to forecast a broad range of mental disorders well in advance of their emergence. (A machine learning approach to predicting psychosis using semantic density and latent content analysis)
An article about the study says:
The results showed that higher than normal usage of words related to sound, combined with a higher rate of using words with similar meaning, meant that psychosis was likely on the horizon. (The whisper of schizophrenia: Machine learning finds ‘sound’ words predict psychosis)
Phillip Wolff, an author of the study, says of it:
“This research is interesting not just for its potential to reveal more about mental illness, but for understanding how the mind works — how it puts ideas together. Machine learning technology is advancing so rapidly that it’s giving us tools to data mine the human mind.” (Ibid)
Auditory Transduction
Informative and well-worth viewing.
Unique American voice: Preacher Kenneth Copeland defends lavish lifestyle