Ginzburg III: On the serendipity engine

Ginzburg explores the role of traces in understanding the world, and usefully repeats the myth of the three sons of the King of Serendippo. The myth is originally found in several folk tales, and roughly goes like this, according to Ginzburg from a 1557 re-telling: the three princes of Serendippo meet a merchant and tells him that they think an animal has passed by. The Merchant, who is missing a camel, asks them to describe the animal and they go onto say that it is a lame camel, blind in one eye, missing a tooth, carrying a pregnant woman, and bearing honey on one side and butter on the other. The merchant then thinks that they, since they know the camel so well, must be the ones who have stolen it – so he charges them. They manage to be acquitted when they show how they by simple inferences together deduced their description.

The genealogical connection to Sherlock Holmes, and the detective story over all, is abundantly clear, and Ginzburg informs us that Horace Walpole later coined the term “serendipty” to refer to cases where “accident and sagacity” allow for knowledge discovery.

Now, in discussions about the web today some have called for more accident – thinking that the increasing focus on filters will create bubbles around us. That, in itself, is an interesting discussion – but not one that Ginzburg engages in. What he does, however, is to suggest that the etymological genealogy of the word presents anyone who wants to design a serendipty engine with two interesting problems.

First, the design of accidents is not trivial. Information follows contexts and simply randomizing information is hardly likely to give the experience of serendipity – it will rather feel like opening your spam email in the hopes of spending time there to become wiser (I just tried that out of curiousity, and did not feel wiser, but rather more misanthropic afterwards). So designing accidental information discovery is one part of the art of building a serendipty engine.

Second, the princes exhibited signficant sagacity. And this presents an even more interesting problem. What if the serendipty engine is not possible without users actively taking an interest in the knowledge and information that they consume? There is a deep problem here, facing those that argue that we need technological fixes to fight off possible filter bubbles. Maybe filters are – to a certain extent – self-imposed products of our own making?

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