Cognitive Analytics and its Black Box theory
When analytics arrived at the stage, everyone was excited and wanted to get to on the bus on the first chance. However, analytics seems to have run its course and it’s looking for new directions in various fields. While there is no immediate and clear-cut solution as of now, but cognitive technology may have opened up a new way for analytics so that it can break across barriers. The new breakthrough that has come in the form of deep learning neural networks or DLNN is going to be change the game altogether, experts predict.
Going beyond human skills
This new technology, as it is being hailed as, can do many things that a capable human mind cannot. They can, once given the necessary commands, recognize all sorts of faces and differentiate, translate various languages and do many more things that an average human being can never do. Moreover, they perform the task brilliantly, and leave no space for errors. Hence, it is surely a challenge.
Why black box?
However, no matter how you would try, you cannot decipher the way they function. It is like a black box where you only see the output once you give the input. The black box works absolutely fine but can never be understood by logical progression of ideas. To put it simply, the way your brain understands what is what and can differentiate one image from the other, it is the same way the network does that effectively.
The fields of resonance
However, there are some fields where it has truly found its potential to be realized such as digital marketing. Of course, the way your Google search can lead you to various advertisements is never a concern of yours, but it is a concerning issue if it comes from the field of banking or healthcare, because they are serious issues. There can be very serious situations where you encounter an inexplicable results and there, you encounter a black box scenario.
The borders of interpretation
Some technologies, however, are quite interpretable such as computational linguistics. Sentence parsing and graphic representation of phrases in a language can be easily deciphered following certain linguistic and computational logic. Such a technology is quite transparent, you need not worry about the black box scenario. While academic work is going on, it still seems to be on a research level as the jargons block the real understanding of the scenario.
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