The Algorithms of Love
Through the ages, the quest to find true love has inspired spells, potions and rituals to give lonely hearts a modicum of certainty. In the world of online dating, though, there is a much more promising charm that hails from the 21st century: the algorithm.
Deployed by sites like eHarmony, Chemistry.com and Match.com, it’s purported to be matchmaking by math, marketed by these companies as a scientific method for finding a compatible mate. If that proposition sounds too good to be true, that’s because it just might be.
Last year, five social scientists took on the idea of the matchmaking algorithm in a lengthy paper that criticized dating sites for making scientific claims without subjecting their formulas to public scrutiny or submitting their work to peer review. For a billion-dollar industry, however, that lack of transparency is no surprise.
More important, perhaps, is the debatable idea that two strangers can be paired using a complicated formula that takes into account dozens or hundreds of data points regarding their potential similarity. A formidable challenge to that, and one pointed out by the social scientists last year, is how to account for the tendency of online daters to put forward aspirational versions of themselves that don’t always reflect who they are in the non-digital world.
A couple weeks ago, a paper that I wrote came up in a conversation about pattern recognition with a student studying emergence theory at NYU. In the paper, I investigated Hausdorff dimension analysis of tree branches to derive their fractal dimension (fractals have a non-integer dimension) as a method of species differentiation and identification. As the bar graph indicates, my efforts were mostly successful, though the lack of a guarantee of dimensional uniqueness calls into question the ultimate utility of the approach.
My original paper can be found here.
I collect Google Earth images. I discovered strange moments where the illusion of a seamless representation of the Earth’s surface seems to break down. At first, I thought they were glitches, or errors in the algorithm, but looking closer I realized the situation was actually more interesting — these images are not glitches. They are the absolute logical result of the system. They are an edge condition—an anomaly within the system, a nonstandard, an outlier, even, but not an error. These jarring moments expose how Google Earth works, focusing our attention on the software. They reveal a new model of representation: not through indexical photographs but through automated data collection from a myriad of different sources constantly updated and endlessly combined to create a seamless illusion; Google Earth is a database disguised as a photographic representation. These uncanny images focus our attention on that process itself, and the network of algorithms, computers, storage systems, automated cameras, maps, pilots, engineers, photographers, surveyors and map-makers that generate them.
Via Clement Valla
JUST WHEN YOU THOUGHT YOU HAD SURELY SEEN THE CUTEST OWL EVER ALREADY YOU FIND YOU ARE WRONG!
(via daneenn)
