Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

February 22, 2013

“…the flawed man versus machine dichotomy”

Filed under: Artificial Intelligence,BigData — Patrick Durusau @ 6:50 am

The backlash against Big Data has started

Kaiser Fung critiques a recent criticism of big data saying:

Andrew Gelman has a beef with David Brooks over his New York Times column called “What Data Can’t Do”. (link) I will get to Brooks’s critique soon–my overall feeling is, he created a bunch of sound bites, and could have benefited from interviewing people like Andrew and myself, who are skeptical of Big Data claims but not maniacally dismissive.

The biggest issue with Brooks’s column is the incessant use of the flawed man versus machine dichotomy. He warns: “It’s foolish to swap the amazing machine in your skull for the crude machine on your desk.” The machine he has in his mind is the science-fictional, self-sufficient, intelligent computer, as opposed to the algorithmic, dumb-and-dumber computer as it exists today and for the last many decades. A more appropriate analogy of today’s computer (and of the foreseeable future) is a machine that the human brain creates to automate mechanical, repetitious tasks at scale. This machine cannot function without human piloting so it’s man versus man-plus-machine, not man versus machine. (emphasis added)

I would have to plead guilty to falling into that “…flawed man versus machine dichotomy.”

And why not?

When machinery gives absurd answers, such as matching children to wanted terrorists and their human counterparts, blindly accept the conclusion, there is cause for concern.

Kaiser concludes:

Brooks made a really great point at the end of the piece, which I will paraphrase: any useful data is cooked. “The end result looks disinterested, but, in reality, there are value choices all the way through, from construction to interpretation.” Instead of thinking about this as cause for concern, we should celebrate these “value choices” because they make the data more useful.

This brings me back to Gelman’s reaction in which he differentiates between good analysis and bad analysis. Except for the simplest problems, any good analysis uses cooked data but an analysis using cooked data could be good or bad.

Perhaps my criticism should be of people who conceal their “value choices” amidst machinery.

There may be disinterested machines, but only the the absence of people and their input.

Yes?

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