Databases Reference
In-Depth Information
that run our data sets; they can be “groundtruthed” to some extent—though increasingly
scientific models are compared primarily against other models. So let's take the unnec-
essary human out of the equation and talk about the program-data-program or data-
program-data cycles.
There is of course an ongoing relationship with the real world and the human
observer (nature and society), however it is a difficult one to express. Both the natural
world and its human observers are being ever more instrumented with intelligent
machines. Staggering arrays of sensors and cameras furbish “us” with terabytes of data
a day about the natural world and about our social activities. The “quantified self ” move-
ment is an oddly worshipful effort to celebrate this quantification (computers do not
deal with “soft” data). The qualified self seems to be slipping out of the picture—the
interpretative work is done inside the computer and read out and acted on by humans.
A dark vision is that our interaction with the world and each other is being rendered
epiphenomenal to these data-program-data cycles. If it's not in principle measurable,
or is not being measured, it doesn't exist. Thus in the natural world, we have largely as
a species elected to take the quantifiable genome (https://www.23andme.com) as the
measure of all life: when we save species (in seedbanks for example), we are saving
irreducible genetic information—not communities (despite the fact that every indi-
vidual comes with its own internal flora and fauna central to its survival; and that each
individual can be understood equally as the product of a network of relationships).
Collectivities that are not being measured and modeled are preserved, if at all, only
accidentally. As people we are, in Olga Kuchinskaya's memorable phrase, becoming our
own data. Mental disorders are less complexes than strings of measurable effects. By
making them data, response regimes can be tested and implemented. However, this
does not mean that completely different understandings of these disorders are not
right—just that the complex, tight coupling between machines in the clinical and
insurance industries and in administration entails that in order to survive in the world,
we need to be able to become data within a highly ramified system. If you are not
data, you don't exist: and just like the unfortunate Doc Daneeka in
Catch 22
, it doesn ' t
really matter how often you declare yourself alive. In the old days of science studies,
we used to worry about the supremacy of the hard sciences, which we rightly tied to
the absolutism of the Christian theology they supplanted. Now we risk being in the grip
of hard data.
This playful, insightful book offers a rather gentler path forward. If data are so central
to our lives and our planet, then we need to understand just what they are and what
