Tag Archives: Algorithms

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.

Digital Welfare Systems

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.

Limits of trustbuilding as policy objective

Yesterday, I attended a virtual event hosted by CIGI and ISPI entitled “Digital Technologies: Building Global Trust”. Some interesting points raised by the panel: the focus on datafication as the central aspect of the digital transformation, and the consequent need to concentrate on the norms, institutions, and emerging professions surrounding the practice of data (re-)use [Stefaan Verhulst, GovLab]; the importance of underlying human connections and behaviors as necessary trust markers [Andrew Wyckoff, OECD]; the distinction between content, data, competition, and physical infrastructure as flashpoints for trust in the technology sphere [Heidi Tworek, UBC]. Also, I learned about the OECD AI Principles (2019), which I had not run across before.

While the breadth of different sectoral interests and use-cases considered by the panel was significant, the framework for analysis (actionable policy solutions to boost trust) ended up being rather limiting. For instance, communal distrust of dominant narratives was considered only from the perspective of deficits of inclusivity (on the part of the authorities) or of digital literacy (on the part of the distrusters). Technical, policy fixes can be a reductive lens through which to see the problem of lack of trust: such an approach misses both the fundamental compulsion to trust that typically underlies the debate, and also the performative effects sought by public manifestations of distrust.

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.

Coded Bias

I managed to catch a screening of the new Shalini Kantayya documentary, Coded Bias, through EDRi. It tells the story of Joy Bualomwini‘s discovery of systematic discrepancies in the performance of algorithms across races and genders. The tone was lively and accessible, with a good tempo, and the cast of characters presented did a good job showcasing a cross-section of female voices in the tech policy space. It was particularly good to see several authors that appear on my syllabus, such as Cathy O’Neil, Zeynep Tufekci, and Virginia Eubanks.