Thursday, June 10, 2021

AI/ML Hype: If even Google doesn't get it right, then...?

 I'm a happy and frequent user of Google Photos, which I use to back up, share, and edit the many photos that I take on my smartphone.

This morning, the mobile app greeted me with a new feature: It suggested that six of my photos were incorrectly oriented, and offered me to fix that by rotating them.

I checked, and out of those six photos, five were totally fine as they were. (I'm a bit pedantic and usually fix any wrong orientation quickly by hand, which Google Photos makes quite easy.)

The sixth was indeed misoriented, but the rotation suggested by the tool was also wrong.

First I laughed. If Google—of all people!—sends me twelve predictions via a highly popular app, and gets eleven of those wrong, how can anybody really expect that Artificial Intelligence/Machine Learning will solve real problems and eventually pay back all the investments being made in it? And note that the problem class here is basically image classification, which is one of the few narrow domains where ML has been particularly effective.

And then I dutifully corrected Google's mispredictions by rotating the proposed images until they were correct (correct again, in five of the six cases). So maybe if a few million other nice/gullible people help poor Google out, then maybe one day, it will actually become helpful even to pedants like me.

This suddenly recalled a question Prof. Mireille Hildebrandt asked at a large EU event last week ("Leading the Digital Decade", video):

What is a digitally skilled population? Is it a population capable of using AI and other digital systems? That's the usual way to talk about citizens: users. Or is it, perhaps, a population that is open to be used by these systems as data engines?

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