Monthly Archives: October 2020

Domestic politics and elections

Robocalling campaigns

Politico‘s Morning Tech reports that the Trump campaign has launched a poll on its website to gauge sentiment as to Twitter’s anti-conservative bias. There is nothing particularly scientific or informative about the poll. In fact, MT speculates that the main purpose of the stunt is to get respondents to agree, in passing, to have their phone numbers robocalled by the campaign (this kind of data-collection-and-authorization has been done before). Robocalling is one of those annoying-but-effective psychological prods, like canned laughter. Participants in the Twitter poll can safely be considered strong fans of the President, but even they might not consent to being robocalled if asked directly, hence this circuitous route. It is remarkable, though, how outrage is commodified as data harvesting, or –seen the other way– how subjection to invasive marketing is the price of interaction with curated forms of political venting.

Comparative and international policy-making

Enforcement as deflection

Technology policy is often characterized as an area in which governments play catch-up, both cognitively and resource-wise, with the private sector. In these two recent cases, otherwise quite far apart both spatially and thematically, law enforcement can be seen to flip this script by attempting to pin responsibility for social externalities on those it can reliably target: the victims and the small fry. Whether it is criminalizing those who pay to be rid of ransomware or rounding up the café owners who failed to participate in the State’s mass surveillance initiatives, the authorities signal the seriousness of their intentions with regards to combating social ills by targeting bystanders rather than the actual perpetrators. Politically, this is a myopic strategy, and I would not be surprised if it generated a significant amount of pushback.

Political economy and visibility

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.