Consider the case of a big-data store the was able to store all of the individual answers keyed with sequence numbers, time stamps, and specific individual identification. I don’t think anyone would voluntarily discard that data in exchange with anonymized data consisting of just a few categories. The value of data reduction into categories is for people who don’t have access to big data. Those people are the consumers who wish to have an external assessment of what kind of person they are, allowing them a shortcut to introducing themselves, similar to the 1960’s approaching of introducing oneself as a zodiacal sign.
These cases are often described as open-secrets. Many people in the community are aware of the information about individual cases and about the pattern of behavior, but there has been some kind of understanding that the past events are resolved in some acceptable terms, and that ongoing behavior is restrained by certain conditions. The oxymoron of open-secrets can be resolved by defining the open-part as being observed data, while the secret-part is restraints on how this data may be used in future decision making.
We should learn from recent experience of large data technologies the lesson that decision making can benefit from streaming data in addition to (and often instead of) the publication science of one-time experiments. It is clear now that policy making needs access to a continuous stream fresh data about old ideas, especially when that data accumulates over time. With access to the technologies to do this work, it is unacceptable to base policies on the failed approaches of the past that rely on published studies.
The title is a play on words from the analogy of the supposed hierarchy structures of wolf packs with alpha males, beta males, and omega males where roughly speaking the alpha males lead the pack and get first choice of resources, the beta males are cooperative and share resources more equitably, and the omega (or…
Unlike skepticism of knowledge or of ability to know the truth, the modern skepticism is a skepticism of having enough data.
IQ data is similar to bright ultraviolet light: it can provide very good illumination (with compatible sensors) but it must be used with abundant caution. Fine-resolution IQ discrimination must result in major implications for the culture, if that discrimination is occurring. I believe it is occurring with the emerging social specialization of an emerging human hive.
The above video presents four eras of human communication from an evolutionary perspective where there was a long time when humans only gestured and grunted, then there was a long time when humans spoke but did not write, then a long time when people wrote. The useful information is the progression of information content possible with each era. The unnecessary information is evolutionary explanation. For this discussion to work, there doesn’t have to be a specific period of time when human culture flourished with illiterate people fluent in verbal languages. There are clearly expansions of content starting with gestures, then adding verbal languages, then adding written languages. The Internet era allows us to publish and retrieve information separately from the story-telling.