Tag Archives: Elections

Workshopping trust and speech at EDMO

It was a great pleasure to convene a workshop at the European Digital Media Observatory today featuring Claire Wardle (Brown), Craig Matasick (OECD), Daniela Stockmann (Hertie), Kalypso Nicolaidis (Oxford), Lisa Ginsborg (EUI), Emma Briant (Bard) and (briefly) Alicia Wanless (Carnegie Endowment for International Peace). The title was “Information flows and institutional reputation: leveraging social trust in times of crisis” and the far-ranging discussion touched on disinformation, trust vs. trustworthiness, different models of content moderation, institutional design, preemptive red-teaming of policies, algorithmic amplification, and the successes and limits of multi-stakeholder frameworks. A very productive meeting, with more to come in the near future on this front.

Russian pre-electoral disinformation in Italy

An interesting blog post by the Institute for Strategic Dialogue discusses Russian propaganda in the run-up to the recent Italian general elections.

Basically, the study identifies 500 Twitter accounts of super-sharers of Russian propaganda in Italian and plots their sentiments with regard to party politics, the conflict in Ukraine, and health/pandemic-response policy during the electoral campaign. This is not, therefore, a network of coordinated inauthentic behavior, but rather a bona fide consumption of Russian propaganda.

There are some interesting takeaways from the data, the main one being the catalyst function of coverage of the Covid-19 response: a significant proportion of users in the group began sharing content from Russian propaganda websites in the context of vaccine hesitancy and resistance to public health measures such as the “green pass“, and then stayed on for Ukraine and Italian election news.

What remains unclear, however, is the extent of the influence in question. The examples given of Kremlin-friendly messages hardly suggest viewpoints without grassroots support in the country: it is fairly easy, for instance, to find the same arguments voiced by mainstream news outlets without any suspicion of collusion with Russia. Also, the analysis of candidate valence does not support the conclusion of a successful misinformation campaign: the eventual winner of the election, Giorgia Meloni, comes in for similar amounts of opprobrium as the liberal establishment Partito Democratico, while the two major parties portrayed in a positive light, Matteo Salvini’s Lega and the 5 Star Movement, were punished at the polls. Perhaps the aspect of the political views of the group that was most attuned to the mood of the electorate was a generalized skepticism of the entire process: #iononvoto (#IDontVote) was a prominent hashtag among these users, and in the end more than a third of eligible voters did just that on September 25th (turnout was down 9% from the 2018 elections). But, again, antipolitical sentiment has deep roots in Italian political culture, well beyond what can be ascribed to Russian meddling.

In the end, faced with the evidence presented by the ISD study one is left with some doubt regarding the direction of causation: were RT and the other Kremlin-friendly outlets steering the political beliefs of users and thus influencing Italian public discourse, or were they merely providing content in agreement with what these users already believed, in order to increase their readership?

Rightwing algorithms?

A long blog post on Olivier Ertzscheid’s personal website [in French] tackles the ideological orientation of the major social media platforms from a variety of points of view (the political leanings of software developers, of bosses, of companies, the politics of content moderation, political correctness, the revolving door with government and political parties, the intrinsic suitability of different ideologies to algorithmic amplification, and so forth).

The conclusions are quite provocative: although algorithms and social media platforms are both demonstrably biased and possessed of independent causal agency, amplifying, steering, and coarsening our public debate, in the end it is simply those with greater resources, material, social, cultural, etc., whose voices are amplified. Algorithms skew to the right because so does our society.

A global take on the mistrust moment

My forthcoming piece on Ethan Zuckerman’s Mistrust: Why Losing Faith in Institutions Provides the Tools to Transform Them for the Italian Political Science Review.

Bridle’s vision

Belatedly finished reading James Bridle’s book New Dark Age: Technology and the End of the Future (Verso, 2018). As the title suggests, the text is systemically pessimist about the effect of new technologies on the sustainability of human wellbeing. Although the overall structure of the argument is at times clouded over by sudden twists in narrative and the sheer variety of anecdotes, there are many hidden gems. I very much enjoyed the idea, borrowed from Timothy Morton, of a hyperobject:

a thing that surrounds us, envelops and entangles us, but that is literally too big to see in its entirety. Mostly, we perceive hyperobjects through their influence on other things […] Because they are so close and yet so hard to see, they defy our ability to describe them rationally, and to master or overcome them in any traditional sense. Climate change is a hyperobject, but so is nuclear radiation, evolution, and the internet.

One of the main characteristics of hyperobjects is that we only ever perceive their imprints on other things, and thus to model the hyperobject requires vast amounts of computation. It can only be appreciated at the network level, made sensible through vast distributed systems of sensors, exabytes of data and computation, performed in time as well as space. Scientific record keeping thus becomes a form of extrasensory perception: a networked, communal, time-travelling knowledge making. (73)

Bridle has some thought-provoking ideas about possible responses to the dehumanizing forces of automation and algorithmic sorting, as well. Particularly captivating was his description of Gary Kasparov’s reaction to defeat at the hands of AI Deep Blue in 1997: the grandmaster proposed ‘Advanced Chess’ tournaments, pitting pairs of human and computer players, since such a pairing is superior to both human and machine players on their own. This type of ‘centaur strategy’ is not simply a winning one: it may, Bridle suggests, hold ethical insights on patways of human adaptation to an era of ubiquitous computation.