Generative AI and pain points

The power of Generative AI to ease the pain of drudgery

And that’s exactly the promise Generative AI holds — it can offer ways to take the drudgery out of many everyday experiences, enabling and empowering people to be better, faster, and more effective.

For example, take any situation where people need to sort through massive amounts of data to identify important insights to take action on. Because people tend to get tired and occasionally make mistakes, in areas like scanning for banking fraud patterns, even small human errors can end up costing banks untold billions of dollars. But Generative AI never gets tired, and can comb through mountains of data and pinpoint anomalies rapidly without error.

But what about Generative AI’s massive potential to create totally new creative content, from articles, screenplays, and marketing campaigns, to music and images?

From “Generative AI: A Creative New World,” via Sequoia Capital
The biggest promise and threat of Generative AI — new content creation

And this really is the biggest shift Generative AI represents — for the first time, we have technology that can be prompted to create something that’s never existed before.

But keep in mind that Generative AI will never make people obsolete. They’ll only be made obsolete by other people who know how to skillfully prompt great Generative AI-powered products to take advantage of its powerful “multiplier” effects.

For better or worse, Generative AI’s incredible potential for content creation is so feared that it’s at the center of the currently ongoing writers & actors dispute that’s now turned into the longest labor dispute of its kind.

While much of that potential is as of yet untapped, at its worst, Generative AI remains largely unreliable, still prone to “hallucinations.”

And when not skillfully prompted, it typically writes weak, trite, and flat-out factually incorrect garbage which clearly wasn’t written by anyone who cares, nor fit for human consumption.

AI needs a clear data strategy, data understanding, a data product analysis, end user analysis and clear value stream mapping.