If anyone still doubted that Agamben’s thesis - according to which biopolitics today is about the reduction of politics to biological existence (zoe), shorn of anything to do with the form (bios) of life – needs revision, this arrives about big-data employee screening that operates with an amalgam of questionnaires and biometrics. Salon’s Andrew Leonard relates:
“Welcome to your next job interview. Because that’s exactly how I felt moments before launching into a set of “cognitive video games” devised by the “employment assessment” company Prophecy Sciences. My pulse was spiking because more was at stake than the life of my avatar. Prophesy Sciences intended to use the data I generated while gaming to determine what kind of worker I was.
Staffed by a handful of Stanford neuroscience Ph.D.s, Prophecy Sciences is an ambitious recent arrival in the fast-growing world of “people analytics.” Prophecy Sciences believes better data is the key to helping employers match the right jobs to the right workers, and even to assemble teams in which employees are guaranteed to be compatible with each other.
The notion that our mental makeup and employment suitability can be analyzed by data gathered from our physiological and behavioral responses to a video game is, to some people, a bit more creepy than a pee test. When I wrote about this phenomenon in December, I wondered if companies like Prophecy Sciences were leading society down the path to a rigid algorithmically-driven meritocracy. What happens to our lives when the machines know us better than we know ourselves?”
There’s a lot that could be said about this so-called “people analytics,” but I’ll confine myself to a few, brief thoughts.
First, it is widely noted that neoliberalism involves the transfer of risk and precarity away from corporations and to workers. This would seem an almost perfect example: workers are responsible for their physiological responses to questions, and corporations will be able to claim that they know in advance how effective an employee will be (note that I haven’t said that employers are any good at using their risk models, or that those models are themselves any good. The financial crisis should be enough to establish serious doubt in that regard, and faith in the models can look more like a moral position than an epistemological one). In this inverse-Rawlsian world, we let natural accidents dictate life as much as possible. People analytics is just the next step in the steady intensification of a process where employers demand complete access to a worker’s life, not just during the job, but as a prior condition for employment; the arc runs from 1980s drug-testing (for convenience store clerks!) to demands that prospective employees share their facebook passwords, now to the collection of biometric data.
Second, we can expect a parallel intensification of efforts at subjectification: workers are to embrace this new world of people analytics, and there will soon enough be a flood of self-help books designed to ease the process of making oneself conform, as much as possible, to the new demands of capital.
Third, defenders of big data like to point out that it’s “more fair” than whatever regime we have now. This is because data, like structural law, enforces uniformly and without human intervention. While it’s certainly true that non-data-driven hiring is full of dubious practices, biases and so forth, we should be very careful in asserting that so-called data-driven approaches are somehow (therefore) more fair. Throwing numbers around is a typical strategy of depoliticization, especially when it’s in the service of turning uncertainty into risk. The old computer science “garbage in, garbage out” principle applies: it is easy enough to build biases into systems. For example, a policy to replace police officers with traffic cameras looks a lot less fair if it turns out that most of those traffic cameras get put into poor neighborhoods. Data may change where we look for bias, or how we ask questions about it, but it doesn’t eliminate them.
Finally, when Leonard gets his results back, the system says he would do best at creative and entrepreneurial jobs. Nothing in the public sector shows up at all. Not that this is a surprise. Maybe they just don't have that in the database yet...