Advances in information and communications technology and the “datafication” of broadening fields of human endeavor are generating unparalleled quantities and kinds of data about individual and group behavior, much of which is now being deployed to assess risk by governments worldwide. For example, law enforcement personnel are expected to prevent terrorism through data-informed policing aimed at curbing extremism before it expresses itself as violence. And police are deployed to predicted “hot spots” based on data related to past crime. Judges are turning to data-driven metrics to help them assess the risk that an individual will act violently and should be detained before trial. 

Where some analysts celebrate these developments as advancing “evidence-based” policing and objective decision-making, others decry the discriminatory impact of reliance on data sets tainted by disproportionate policing in communities of color. Still others insist on a bright line between policing for community safety in countries with democratic traditions and credible institutions, and policing for social control in authoritarian settings. The 2016 annual conference will . . . consider the human rights implications of the varied uses of predictive analytics by state actors. As a core part of this endeavor, the conference will examine—and seek to advance—the capacity of human rights practitioners to access, evaluate, and challenge risk assessments made through predictive analytics by governments worldwide. 

According to Agamben, the signature of a state of exception is 'force-of'; actions that have the force of law even when not of the law. Software is being used to predict which people on parole or probation are most likely to commit murder or other crimes. The algorithms developed by university researchers uses a dataset of 60,000 crimes and some dozens of variables about the individuals to help determine how much supervision the parolees should have. While having discriminatory potential, this algorithm is being invoked within a legal context. 

[T]he steep rise in the rate of drone attacks during the Obama administration has been ascribed to the algorithmic identification of 'risky subjects' via the disposition matrix. According to interviews with US national security officials the disposition matrix contains the names of terrorism suspects arrayed against other factors derived from data in 'a single, continually evolving database in which biographies, locations, known associates and affiliated organizations are all catalogued.' Seen through the lens of states of exception, we cannot assume that the impact of algorithmic force-of will be constrained because we do not live in a dictatorship. . . .What we need to be alert for, according to Agamben, is not a confusion of legislative and executive powers but separation of law and force of law. . . . [P]redictive algorithms increasingly manifest as a force-of which cannot be restrained by invoking privacy or data protection. 

To some extent, the fears of men in a hyperconnected era reflect all-too-familiar experiences of women. Being objects of surveillance and control, exhausting laboring without rewards and being lost through the holes of the meritocracy net, being constrained in a specular posture of other’s deeds: all these stances have been the fate of women’s lives for centuries, if not millennia. What men fear from the State or from “Big (br)Other”, they have experienced with men. So, welcome to world of women….