Researchers reveal two different attempts to out-smart the Rothko and Warhol markets with machine learning; Victoria Miro holds back.

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The Rise of the Machines

The desire to invent a machine that can predict the future behavior of markets, random events like horse races or casino games seems to be nearly inexhaustible. The discovery of machine learning has only renewed interest in that desire. Predicting the prices of art works is now becoming a popular pastime for the mathematically minded. who believe that enough data run through our near limitless computing capacity can can possibly reveal patterns that will predict price better than knowledge and experience. You might have thought these efforts were still somewhat in the realm of spec scripts for movie thrillers or academic test cases. But today we have two different attempts to predict prices for next week’s marquee auctions of Contemporary art. On the one hand, we have a group looking at a few Mark Rothko prices; on the other, we have an art market start up running a bake on the whole Warhol market. We won’t know whether to take either of these seriously until next week. Even then, we should take care not to be fooled by randomness, as Nassim Taleb tells us, and assume that a single set of predictions constitutes a meaningful tool. Nonetheless, let’s start with Rothko and then move on to Warhol.