The AI bubble is deflating and disillusionment is starting to set in. But insiders and Wall Street analysts say there’s hope yet. AI Eye.
It’s fair to say that the initial hype bubble around AI has burst, and people are starting to ask: What has AI done for me lately?
Too often, the answer is not much. A study in the Journal of Hospitality Marketing & Management found that products described as using AI are consistently less popular. The effect is even more pronounced with high-risk purchases like expensive electronics or medical devices, suggesting consumers have serious reservations about the reliability of current AI tech.
“When AI is mentioned, it tends to lower emotional trust, which in turn decreases purchase intentions,” said lead author and Washington State University clinical assistant professor of marketing Mesut Cicek.
Workplaces are also finding that AI technology’s enormous potential is not yet being delivered. A study from the Upwork Research Institute found that 77% of workers who use AI say the tools have decreased their productivity and added to their workload in at least one way.
And that’s among the businesses who actually use it: according to the US Census Bureau, only about 5% of businesses have used AI in the past fortnight.
Rune Christensen’s grand Endgame plans (as outlined in Magazine earlier this year) to make MakerDAO genuinely autonomous by handing much of the coordination to AI has also been shelved. Just one of four new subDAOs scheduled to launch this year will — SparkDAO — because AI governance isn’t up to the workload.
“AI is really great most of the time, but it also has a lot of hidden errors and small issues that make it unreliable,” Christensen told DL News.
This is the issue in a nutshell. AI may be correct 97% of the time, but that isn’t reliable enough for most critical operations. You wouldn’t get on a plane that only lands successfully 97% of the time, just as you wouldn’t risk a mission-critical business with it.
So AI may have entered the “trough of disillusionment” phase of the Gartner Hype Cycle* where interest wanes as experiments and implementations fail to deliver on the hype.
(*Research suggests most new technologies don’t play out as the hype cycle suggests. Think of it as a nice metaphor or something.)
Source: Cointelegraph
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