Tag Archives: Algorithms

Tropes of the Techlash

A review by Paul Dicken published online a week ago in The New Atlantis is representative of a certain kind of argument in contemporary social critiques of high tech. The piece discusses a book by Ben Schneiderman entitled Human-Centered AI, which came out earlier this year for Oxford UP, and mainly reads as an exposé of a benighted scientism that at best is hopelessly naïve about its potential to effect meaningful emancipatory social change and at worst is disingenuous about the extractive and exploitative agendas that underwrite its deployment.

One would not wish to deny that Schneiderman makes for a good target: computer scientists as a sociological class are hardly more self-reflexive or engagé than any other similarly-defined professional group, and divulgative AI-and-management texts seldom present incisive and counterintuitive social commentary. Nonetheless, it is hard to miss a certain symmetry between the attacks on the political self-awareness of the author in question (how could he have missed the damning social implications??) and the peans to progress through techno-solutionism which characterized public debate on Web2.0 before the techlash.

The fact itself that Dicken refers back to Charles Babbage as a precursor of contemporary AI research and its dark side should suggest that the entwinement of technological advancement with political economy might be a long-run phenomenon. What is different is that in the present conjuncture would-be social critics seem to harbor absolutely no faith that the political and social ills upstream from technological development can be righted, and no plan to do so. New technology changes affordances, and this shift makes certain social dynamics more visible. But in the absence of specifically political work, such visibility is ephemeral, irrelevant. Hence, the exposé of political cluelessness risks becoming the master trope of the techlash, essentially a declaration of social impotence.

A.utomated I.dentity?

An interesting, thoughtful article by Michelle Santiago Cortés in The Cut last week looks at affective relationships with algorithms and their role in shaping our identities.

Three parts of the analysis specifically stood out to me. The first revolves around our typical lack of knowledge of algorithms: Cortés’ story about

some YouTube alpha male […] out there uploading videos promising straight men advice on how to “hack” the Tinder algorithm to date like kings

is clearly only the tip of a gigantic societal iceberg, a cargo-culture-as-way-of-life involving pretty much everyone in the remotest, most diverse walks of life. The ever-evolving nature of these algorithms compounds the obfuscation effect, making end-users’ strategic attempts, whether exploitation- or resistance-focused, generally appear puerile.

Second, the clarity with which Cortés encapsulated the main tradeoff in the relationship was truly apt:

[w]e are, to varying degrees, okay with being surveilled as long as we get to feel seen.

The assertion of visibility and assurance of recognition are two of the key assets algorithmic systems offer their users, and their value can hardly be minimized as mere late-consumerist narcissism.

Finally, the comparison between algorithmic portraits of personality and astrology was extremely telling: closing the behavioral loop from algorithmic interaction to the redefinition of one’s own identity on the basis of the algorithm’s inevitably distorting mirror is still a matter of choice, or rather, a sensibility that can be honed and socialized regarding the most empowering and nurturing use of what is ultimately a hermeneutic tool. Of course, such a benign conclusion rests on the ambit of application of such technologies: music videos, entertainment, dating. As soon as our contemporary astrological devices are put in charge of directing outcomes in the field of political economy and public policy, the moral calculus rapidly shifts.

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.