Information underload – Mike Caulfied on the limits of #Watson, #AI and #BigData

The piece linked to here has applications well beyond medicine and the specific diagnostic issues with Watson – some much of the hype of Big Data is predicated on the quality of the Big Data itself being unquestionable.

A Medical Education

From Mike Caufield, a piece that reminds me of the adage Garbage In, Garbage Out:

For many years, the underlying thesis of the tech world has been that there is too much information and therefore we need technology to surface the best information. In the mid 2000s, that technology was pitched as Web 2.0. Nowadays, the solution is supposedly AI.

I’m increasingly convinced, however, that our problem is not information overload but information underload. We suffer not because there is just too much good information out there to process, but because most information out there is low quality slapdash takes on low quality research, endlessly pinging around the spin-o-sphere.

Take, for instance, the latest news on Watson. Watson, you might remember, was IBM’s former AI-based Jeopardy winner that was going to go from “Who is David McCullough?” to curing cancer.

So how has this worked out? Four years later, Watson…

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