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1. What in the Name of ML and AI!

Updated: Jun 16, 2020

This article is Talk 01 ofHonest Data Science Talksseries. Each talk of around 500 words length, is personal thoughts and deliberations on the domain.

I met these people from a company that claimed to have been teaching AI (Artificial Intelligence) and ML (Machine Learning) to school kids and teachers. No, not even to high school but to lower and primary. Being curious to know what the program was all about, surprisingly, most of it was using a website with simple animation buttons to move objects up and down. I had seen such sites (exactly same ones) and tools earlier and they were not new inventions. What worried me most was that AI being labelled as basic programming. Okay, the much more significant concern was fooling out a community of people who really aren’t aware of AI and falsifying the conceptual background.

I pity the universities for once who taught Data Mining and Analysis, renamed the same syllabus to Business Intelligence and Analytics over the years, and then renamed the same to Machine Learning and now calling it as Artificial Intelligence (wow!). You ask me what? Surprisingly, the textbook/content for all four is almost the same. I know it’s a LOL moment (ROFL maybe). Oh, okay, no, I pity the students. I pity the new generations which have been forsaken with old things on a new name.

Using a statistical algorithm already known for years on different data sets and then publishing a paper with graphs and analysis (not really analysis) with specific data results cannot qualify for ML or AI research. Using an API, not knowing what it does internally and presenting the results is not AI. In one of the conferences I attended, swarm Intelligence results were compared with another API result not related to and presented that the latter did better. The presenter had no idea what swarm intelligence did as the inbuilt API did everything! To the hell, that it was never questioned and was accepted with no interventions. The sad state of affairs is that it’s going to be someone’s published research work under a degree program.

Doing it because everyone is doing is not intelligence. Maybe that is artificial intelligence heavily stressing on ‘artificial’ which is damn away from ‘natural’.

Restarting an old dumped project and branding under Smart Application is not really AI.  A smart city does not mean that it requires an ML or AI solution. A data scientist can never be certified with AI for there can be no one constant syllabus that certifies that, in the true meaning of its name. Using programming language tools to train and test and then predict with a probability is probably NOT AI at all.

It’s not a question of one’s work’s authenticity or credibility. It’s a question of branding and labelling. Are we doing the right thing is the question to ask. This pretty much reminds me of a phrase I had read somewhere which said – to verify if ‘m’ was silent in ‘masses’ that you followed.

I am sure that the AI is crying out somewhere to the ear-less community.

AI, as I understand, is NOT about machine intelligence. It’s about human intelligence. As long as we are not programming the machine to behave dumb and stupid, we are not programming humans. 

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