Tag Archives: Algorithms

Hiding

Given the recent salience of news on surveillance and surveillance capitalism, it is to be expected that there would be rising interest in material, technical countermeasures. Indeed, a cottage industry of surveillance-avoidance gear and gadgetry has sprung up. The reviews of these apparatuses tend to agree that the results they achieve are not great. For one thing, they are typically targeted at one type of surveillance vector at a time, thus requiring a specifically tailored attack model rather than being comprehensive solutions. Moreover, they can really only be fine-tuned properly if they have access to the source code of the algorithm they are trying to beat, or at least can test its response in controlled conditions before facing it in the wild. But of course, uncertainty about the outcomes of surveillance, or indeed about whether it is taking place to begin with, is the heart of the matter.

The creators of these countermeasures themselves, whatever their personal intellectual commitment to privacy and anonymity, hardly follow their own advice in eschewing the visibility the large internet platforms afford. Whether these systems try to beat machine-learning algorithms through data poisoning or adversarial attacks, they tend to be more of a political statement and proof of concept than a workable solution, especially in the long term. In general, even when effective, using these countermeasures is seen as extremely cumbersome and self-penalizing: they can be useful in limited situations for operating in ‘stealth mode’, but cannot be lived in permanently.

If this is the technological state of play, are we destined to a future of much greater personal transparency, or is the notion of hiding undergoing an evolution? Certainly, the momentum behind the diffusion of surveillance techniques such as facial recognition appears massive worldwide. Furthermore, it is no longer merely a question of centralized state agencies: the technology is mature for individual consumers to enact private micro-surveillance. This sea change is certainly prompting shifts in acceptable social behavior. But as to the wider problem of obscurity in our social lives, the strategic response may well lie in a mixture of compartimentalization and hiding in plain sight. And of course systems of any kind are easier to beat when one can target the human agent at the other end.

The hustle and the algorithm

Various interesting new pieces on the experience of the algorithmically-directed gig economy. The proximate cause for interest is the upcoming vote in California on Prop. 22, a gig industry-sponsored ballot initiative to overturn some of the labor protections for gig workers enacted by the California legislature last year with AB 5.

Non-compliance with the regulations enacted by this statute has been widespread and brazen by the market leaders in the gig economy, who now hope to cancel the law directly, using direct democracy (as has often been done by special interests in California in the past). Ride-sharing companies such as Uber and Lyft have threatened to leave the state altogether unless these regulations are dropped, thus putting pressure on their workforce to support the ballot initiative at the polls.

Of course, the exploitative potential in US labor law and relations long pre-dates the platforms and the gig economy. However, with respect to at least some of these firms, it is a legitimate question to ask whether there is any substantial value being produced via technological innovation, or whether their market profitability relies essentially on the ability to squeeze more labor out of their workers.

In this sense, and in parallel with the (COVID-accelerated) transition out of a jobs-based model of employment, the gig economy co-opts the evocative potential of entrepreneurialism, especially in its actually-existing form as the self-exploitation dynamics of American immigrant culture. Also, it is hard to miss the gender and race subtexts of this appeal to entrepreneurialism. As one thoughtful article in Dissent puts it, many of the innovative platforms are really targeted to subprime markets:

[t]he platform economy is a stopgap to overcome exclusion, and a tool used to target people for predatory inclusion.

Hence the algorithm as flashpoint in labor relations: it is where the idealized notion of individual striving and the hustle meets the systemic limits of an extractive economy; its very opacity fuels mistrust in the intentions of the platforms.