Why Do So Few People Seem to Care About the Exaggerations of AI?

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Executive Summary

There is a significant issue with only a small percentage of the population, even in developed countries caring what is true concerning AI/ML.
This article presents evidence that this is the case.

Introduction

The AI/ML bubble has been aggressively hyped for several years now. IT media has been aggressive in promoting the AI/ML bubble, as it has with nearly all technology bubbles, driven by ad revenue and paid placements from industry sources.

What is curious is that even though there are so many horror stories from projects, this bubble has not yet been burst.

Faking AI/ML Benefits

If you look at when AI/ML really took off the third time, I was triggered by Watson winning in Jeopardy. There were improvements in neural networks also –but a huge amount of the bump was due to IBM and then others just getting their smoke and mirror machines working to push out AI/ML. And it worked. It will take years for the stories to come out about how ineffective these projects have been — and how much waste there was. The establishment media will only cover them so that the story can be minimized in terms of who lied and when. And when it peters out, the industry will have moved to blockchain or other XYZ hot topic. The point is never to go back and analyze the past.

If one makes their money from AI/ML, they will want to keep the scam going as long as possible. I cover in this article about Marvin Minsky titled How Accurate Was Marvin Minsky in His AI Predictions? that the establishment media has done a terrible job in covering how much of AI/ML — since its inception, has been based upon false claims.

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Conclusion

I am increasingly coming to the view that a small fraction of the overall population cares what is true. People are searching for ways to make money — not ways they can find out what is true. If you sit on an oversold IBM “AI” project for six months and do nothing but talk about AI and then submit data specs and clean data — you still get paid.

Most people that are working are just working to make money and to attain status in their field. That sounds like a strange thing to say — however, what I mean is that they interpret every statement or assertion not based upon whether it is true or false, or has evidence or does not have proof, but on whether it makes them more money or less money. I recently shared an article, How Common is Research/IP theft in IT, covering the high degree of research theft and lack of references/attribution in private research. It was one of my worst performing shares.

Why?

Well, it does not translate to $$$ but goes to the integrity of private research. If I publish an article on how much opportunity there is in AI/ML, I will get many likes, even with putting little effort into the article. People are searching for ways to make money — not ways they can find out what is true. Work is the place where you “make money,” it is not, too many people, a place where you look for what is true.