DFI is no longer searching for Kala Pahar or Black Top (both actually have a different meaning) ....
Iska matlab hai - Mila Gaya ... Mil Gaya...
This shows what a difference one good factually sound explainer can do to a particular topic, in this case Rohit vats video on Ladakh ranges. what ever answers people were looking for is there somewhere in that video.
In contrast look at the ruckus created on SM by a few retired jernails about the same topic, whatever they communicated and the way they communicated made people go nuts.
I am calling this the OSINT “null ignorance phenomenon”.
1 1 1 1 1
——————————
0 0 0 0 0
Here goes my hypothesis:
If the OSINT data available for analysis is represented by binaries of zero and one, and OSINT expert based on one’s expertise tends to focus on one dataset in this case some of the “1” because they are sniffed out, they are sniffed out because that’s what their training or algorithm is looking for. In the same dataset rest of the 0s are ignored.
But as we all know it takes all the 1s and 0s to get the complete picture, this ignorance of rest of 0s or nulls can be termed as “null ignorance phenomenon”.
result of this phenomenon is that the since only the 1s are presented as the complete data, focus tends to remain on the data presented i.e 1s. any analysis that is based on this set of data presented tends to remain inconclusive.
Hence recognising whether any set of data present by an OSINT analyst or a group of OSINT analysts has an element of “null ignorance” is key to deciding whether the published data is wholesome, or needs further interpretation and analysis by someone who recognises the missing elements of the data presented.
