Why do AI projects fail then?
Good article by Jürgen Geuter:
Why “AI” projects fail
“By some estimates, more than 80 percent of AI projects fail—twice the rate of failure for information technology projects that do not involve AI.” – The Root Causes of Failure for Artificial Intelligence Projects and How They Can Succeed A study by the RAND Corporation (found via David Gerard’s blog) outlines a few key issues […]
tante
“And we’ve been doing this for decades now, with every new technology we spend a lot of money to get a lot of bloody noses for way too little outcome. Because we keep not looking at actual, real problems in front of us – that the people affected by them probably can tell you at least a significant part of the solution to. No we want a magic tool to make the problem disappear. Which is a significantly different thing than solving it.”
He also mentions:
“But even if we said for a second that those tools are great time savers and catalysts of productivity (a fact studies don’t fully support) what do organizations learn here? They added another license to pay for to their balance sheet okay, but does this make the organization more capable in understanding the limitations and capabilities of statistics-based signal processing? Did anyone learn anything?”
And that reminded me of the recently released videos of Rear Admiral Grace Hopper by the NSA. Her talks were from 1982 (She was a Captain at the time). Remarkable woman that I had not heard of. Do look her up. Well worth a watch (and I’m not fond of watching video)
Capt. Grace Hopper on Future Possibilities: Data, Hardware, Software, and People (1982)
On August 26, 2024, the National Security Agency (NSA) released a digital copy of a videotaped lecture, “Future Possibilities: Data, Hardware, Software, and People” that Rear Adm. Grace Hopper gave to
42 years and we’re still talking about the same problems with the underlying solution approach.
What problem are you trying to solve?