With the demand for chips, processors, and memory from AI data centers, there’s a ton of money to be made, and selling small amounts of these same parts to computer enthusiasts is a distraction that isn’t worth the effort.
In the age of AI, though, this might be the high-priority risk. That old, untrustworthy, and outdated information that no one ever bothered to clean up is actively messing up your AI implementation. Your attempt to be a data-driven business depends on having accurate data. That becomes difficult to do when you’re not actively cleaning up after yourself.
It’s no wonder that people are burning out professionally. Every week there are new things to learn, changes to deal with, strategies to reconsider, projects on deadlines, etc. We don’t often get a chance to simply do the work, let alone rest.
I think we might need a variation of the Dunning-Kruger effect to describe the people who weren’t smart enough to realize the AI was wrong when it told them their ideas were brilliant.
Do your users understand the risks and how to use AI safely?