Good News about Big Data and AI: Not Likely
February 25, 2019
I read a write up which was a bit of a downer. The story appeared in Analytics India and was titled “10 Challenges That Data Science Industry Still Faces.” Oh, oh. Maybe not good news?
My first thought was, “Only 10?”
The write up explains that the number one challenge is humans. The idea that smart software would solve these types of problems: Sluggish workers at fast food restaurants, fascinating decisions made by entry level workers in some government bureaus, and the often remarkable statements offered by talking heads on US cable TV “real news” programs, among others.
Nope. The number one challenge is finding humans who can do data science work.
What’s number two after this somewhat thorny problem? The answer is finding the “right data” and then getting a chunk of data one can actually process.
So one and two are what I would call bedrock issues: Expertise and information.
What about the other eight challenges. Here are three of them. I urge you to read the original article for the other five issues.
- Informing people why data science and its related operations are good for you. Is this similar to convincing a three year old that lima beans are just super.
- Storytelling. I think this means, “These data mean…” One hopes the humans (who are in short supply) draw the correct inferences. One hopes.
- Models. This is a shorthand way of saying, “What’s assembled will work.” Hopefully the answer is, “Sure, our models are great.”
Analytics India has taken a risk with their write up. None of the data science acolytes want to hear “bad news.”
Let’s federate and analyze that with great data we can select to generate a useful output. Maybe 80 percent “accuracy” on a good day?
Stephen E Arnold, February 25, 2019
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