Residual problems of intelligence

Modern data science/machine learning/AI has achieved much through efficiently performing certain tasks to an acceptable level of quality. It remains to be seen whether there are means to tackle the residual problems, or perhaps, whether there is the will to do so.

I ran into a couple of problems while using Yelp.

First, I sorted the restaurant reviews by date, and the first two reviews that popped up were these:

These two reviews are almost identical. If we take them at face value, these are two people, one from Midtown West and the other from Staten Island, who both walked in for lunch two days apart (assuming they wrote the review on the same day of their respective meals), and managed to grab one of the last tables. They both ordered steak frites and loved it, especially the fries. And, they both decided to come back for breakfast in the future. They also learned English composition from the same teacher. What a coincidence!

Yelp has long had implemented AI that supposedly detects fake reviews but apparently something that is so obvious is missed by the algorithm.

There's a lot to unpack here but one key immutable fact is that all review sites attract fake reviews because good reviews are great marketing for businesses. Review sites that stringently authenticate reviewers will have much lower volumes of reviews, which creates a negative network effect. Authentication does not solve the root cause anyway, since businesses hire real people to write fake reviews.

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The next situation I ran into isn't really about Yelp but about Google Maps. Within Yelp, I clicked on the address to see the location of a restaurant. I read in one of the reviews that this restaurant is inside a hotel. In order to confirm that, I entered the hotel name and asked for directions inside Google Maps.

Here is the recommended route:

It literally says walk out of the building (the hotel), make a circle around the block, then re-enter the building (the restaurant). It doesn't realize that the beginning and ending addresses are identical.

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It's surprising that these issues persist so many years after these services were launched. Make no mistake - most users have most of their problems solved using Yelp and Google Maps. What's the incentive to solve the residual problems? That's what's on my mind today.

Comments

[Antonio Rinaldi]

Another "residual" problem:
https://twitter.com/TheBabylonBee/status/1648438793610096642