AI at Work: Bubbles in the sand Part II
Wanna crawl through some sludge-lined tunnels?
In Part I of my quickly ballooning1 “AI at Work” series, we walked through some of the ways people use generative AI at work, and highlighted the four primary ways professionals are benefitting from integrating gen AI into their work.
Here in Part II, we get down on our knees and crawl through the less savory aspects of gen AI. Bias. Creator compensation (or rather, lack thereof). The environmental footprint. Identity appropriation. Data labeling sweatshops. And more foul-smelling roses. As those familiar with dragons will tell you, there are benevolent dragons and there are malevolent dragons. And as with any world-changing technology released before its ripening time, things will break. Bones will shatter. Heads will spin. But there’s no other choice but to walk through the fire.
Alright, let’s roll up those sleeves and get to work shall we. There’s a lot of ground to cover. Er, slime-slicked AI dragon burrows to crawl through.
This series lives behind the paywall, so I can feed the insatiable data dragons. But if financial constraints make it challenging for you to upgrade, drop me a line and we’ll work it out—especially if your profession is being impacted by generative AI.
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