Is it, or isn’t it?

Humans are inveterate classifiers. We can’t help ourselves, it seems: we just have to put things in hard-edged categories. Computing might help to blur the edges in a useful way.

An update on the Pluto controversy in New Scientist is a case in point. Discoveries of exoplanets and the anticipation of Earth-size objects in the Kuiper belt make the argument increasingly irrelevant, but yet even professional astronomers seem caught up in arguing for one definition of planets or the other.

Sensory systems like ours are complicated webs of classifiers: whether objects are moving or still, whether movements are animal-like or not, whether something is a face, whether a sound is speech or music, whether someone is a member of our group or not, and endlessly on. Categorization is innate and unavoidable.

But once embedded in culture, it can quickly spiral out into fraught territory. Problems arise because classification has consequences, often monetary, often political. Is that bond AAA or AA? Is that car a clunker or not? Is so-and-so in a special group, or not? Is that judge biased?

The difficulty arises because there are so many parameters that could be used for any classification; people argue about which parameters should count. Does roundness a planet make, or size, or not orbiting around another one, or having swept its orbit clear of other rocks? Cognitive limitations (the four-or-less rule, see e.g. Halford et al. (2004), “How many variables can humans process?” Psychological Science, 16, 70-76) mean that we end up picking a few criteria from the many – too few. And then we require that each criterion must yield a yes/no result, which even for hard science classifications can be contentious: what does it mean for a planet candidate to have “a nearly round shape”?

Computing can help by allowing many more criteria into the mix, and allowing them to vary continuously. This is an application of Edward Tufte’s design strategy “to clarify, add detail,” which he introduces in Envisioning Information (1990, p. 37) with the example of The Isometric Map of Midtown Manhattan. Human nature means we may be a little uneasy with the result, but perhaps we can learn to live with it; most people are comfortable nowadays with weather forecasts that say there’s a 50% chance of rain tomorrow (although many may not actually understand what it means ...).

Hiding the criteria has its own dangers. As Bowker and Star argue in Sorting things out: classification and its consequences (1999), any classification encodes a world view, and even “simple” classification systems succeed in making themselves invisible.

Still, with a little more computing we could, in response to the question “Is it, or isn’t it?” answer in a rigorous way, “Ish.” Computers can handle composing dozens or hundreds of continuous criteria in ways our (conscious) brains cannot.