An extremely interesting series of talks hosted by the Digital Freedom Fund: the automation of welfare system decisons is where the neoliberal agenda and digitalization intersect in the most socially explosive fashion. All six events look good, but I am particularly looking forward to the discussion of the Dutch System Risk Indication (SyRI) scandal on Oct. 27th. More info and free registration on the DFF’s website.
An interesting report in Medium (via /.) discusses the PRC’s new pervasive surveillance program, Sharp Eyes. The program, which complements several other mass surveillance initiatives by the Chinese government, such as SkyNet, is aimed especially at rural communities and small towns. With all the caveats related to the fragmentary nature of the information available to outside researchers, it appears that Sharp Eyes’ main characteristic is being community-driven: the feeds from CCTV cameras monitoring public spaces are made accessible to individuals in the community, whether at home from their TVs and monitors or through smartphone apps. Hence, local communities become responsible for monitoring themselves (and providing denunciations of deviants to the authorities).
This outsourcing of social control is clearly a labor-saving initiative, which itself ties in to a long-run, classic theme in Chinese governance. It is not hard to perceive how such a scheme may encourage social homogeneization and irregimentation dynamics, and be especially effective against stigmatized minorities. After all, the entire system of Chinese official surveillance is more or less formally linked to the controversial Social Credit System, a scoring of the population for ideological and financial conformity.
However, I wonder whether a community-driven surveillance program, in rendering society more transparent to itself, does not also potentially offer accountability tools to civil society vis-à-vis the government. After all, complete visibility of public space by all members of society also can mean exposure and documentation of specific public instances of abuse of authority, such as police brutality. Such cases could of course be blacked out of the feeds, but such a heavy-handed tactic would cut into the propaganda value of the transparency initiative and affect public trust in the system. Alternatively, offending material could be removed more seamlessly through deep fake interventions, but the resources necessary for such a level of tampering, including the additional layer of bureaucracy needed to curate live feeds, would seem ultimately self-defeating in terms of the cost-cutting rationale.
In any case, including the monitored public within the monitoring loop (and emphasizing the collective responsibility aspect of the practice over the atomizing, pervasive-suspicion one) promises to create novel practical and theoretical challenges for mass surveillance.
Vice reports on a Tokyo-based company, DeepScore, pitching software for the automatic recognition of ‘trustworthiness’, e.g. in loan applicants. Although their claimed false-negative rate of 30% may not sound particularly impressive, it must of course be compared to well-known human biases in lending decisions. Perhaps more interesting is the instrumentalization cycle, which is all but assured to take place if DeepScore’s algorithm gains wide acceptance. On the one hand, the algorithm’s goal is to create a precise definition for a broad and vague human characteristic like trustworthiness—that is to say, to operationalize it. Then, if the algorithm is successful on its training sample and becomes adopted by real-world decision-makers, the social power of the adopters reifies the research hypothesis: trustworthiness becomes what the algorithm says it is (because money talks). Thus, the behavioral redefinition of a folk psychology concept comes to fruition. On the other hand, however, instrumentalization immediately kicks in, as users attempt to game the operationalized definition, by managing to present the algorithmically-approved symptoms without the underlying condition (sincerity). Hence, the signal loses strength, and the cycle completes. The fact that DeepScore’s trustworthiness algorithm is intended for credit markets in South-East Asia, where there exist populations without access to traditional credit-scoring channels, merely clarifies the ‘predatory inclusion’ logic of such practices (v. supra).
Josephine Wolff (Slate) reports on the recent hack of the water processing plant in Oldsmar, FL. Unknown intruders remotely accessed the plant’s controls and attempted to increase the lye content of the town’s water supply to potentially lethal levels. The case is notable in that the human fail-safe (the plant operator on duty) successfully counterbalanced the machine vulnerability, catching the hack as it was taking place and overriding the automatic controls, so no real-world adverse effects ultimately occurred.
What moral can be drawn? It is reasonable to argue, as Wolff does, against full automation: human supervision still has a critical role to play in the resiliency of critical control systems through human-machine redundancy. However, what Wolff does not mention is that this modus operandi may itself be interpreted as a signature of sorts (although no attribution has appeared in the press so far): it speaks of amateurism or of a proof-of-concept stunt; in any case, of an actor not planning to do any serious damage. Otherwise, it is highly improbable that there would have been no parallel attempt at social engineering of (or other types of attacks against) on-site technicians. After all, as the old security engineering nostrum states, rookies target technology, pros target people.
I am following (just like everyone else) the developing GameStop story. Beyond the financial technicalities, what is interesting for present purposes is that the dynamics of internet virality seem to be finding a close parallel in stock valuation. The term “meme stock” is telling. In other words, at present the online coordination mechanisms, the capital, and the nihilistic boredom are all available to craft an alternative description of reality, which in turn is self-reinforcing (until it isn’t).