The expression “Garbage In, Garbage Out” emerged in the earliest days of computer science.
A 1957 article on US army mathematicians working with old-school IBM mainframes used the phrase “Garbage In, Garbage Out” to describe how poor quality data inputs lead to poor quality outputs.
The adage has only grown more relevant in our increasingly data-driven world. Our decisions based on data are only as good as the reliability of that data. (View Highlight)
While 76% of business leaders say the rise of AI increases their need to be data-driven, only 36% say they are confident in the accuracy of their company’s data. And that data confidence level has plummeted 27% from 2023.
With ever more powerful AI tools, including AI Agents that act autonomously, the quality of the underlying data matters more than ever. (View Highlight)
I like how Greg Kihlstrom phrased the challenge:
“If your marketing data is fragmented, outdated or riddled with inconsistencies, AI won’t fix the problem; it will just be a faster way to generate confident nonsense.” (View Highlight)
