Last week, I published an essay at Tech Policy Press: We Need an Interventionist Mindset. This essay is targeted at those who are building or governing tech systems, including AI. I am so grateful that they let me publish it there. If you don't mind clicking on the link, do so to give the great people at TPP some link love. But I've also included it below just in case this is the only way you'll read it. <grin>

In other news, I was elected as a fellow to AAAS (the American Association for the Advancement of Science). w000t!

We Need an Interventionist Mindset

Technologists and policymakers have a lot in common. Both seek to find solutions to problems. Both also seek to bend the future to their will. Among practitioners in both worlds, novel and innovative solutions are valorized. However, this also means that both technologists and policymakers tend to fall into traps of their own making. To make matters worse, policymakers tend to harden the solutionist logics of the technology industry in pursuit of regulating it, concretizing their power rather than serving as a check to it.

This talk invites everyone listening to shift their orientation away from solutionism in order to meaningfully challenge the existing arrangement of money and power that configures our contemporary sociotechnical environment. Rather than looking for “solutions,” explore “interventions.” An interventionist framework ensures a more iterative and non-deterministic approach to shaping AI futures.

Identifying Determinism

The concept of determinism can be summed up as the notion that “if X than Y.” Throughout history, as theologians struggled with the existence of God, many philosophers eschewed free will and took a deterministic stance. A deterministic orientation towards the human experience suggests that the future is pre-ordained. At a more micro level, every action produces a knowable outcome.

Engineers and technologists have also repeatedly pursued determinism within their own systems, with little recognition of the ecclesiastical roots of their orientation. Their mechanistic sensibility craves certainty. As such, they want to ensure that, if a person flicks a switch, the outcome is predictable.

Modern-day technologies, however, are often complex sociotechnical systems. This is especially true for systems that interact with unpredictable humans and messy social contexts. While many technologies may be designed to produce a knowable output to a user action, generative AI systems are intentionally designed to be non-deterministic. It may be possible to read the code or know what data a model is trained on. Yet, the power of generative AI stems from the ability to work with so much complexity that the output is probabilistic at every turn.

Even as AI specialists grapple with the conceptual and social consequences of building non-deterministic systems, their rhetoric about these systems’ role in society is trapped by the dominant paradigm of their industry. From the moment that ChatGPT was launched, technologists pronounced inevitable futures. Rather than being challenged, their deterministic prognostications were reinforced by journalists, companies, scholars, and policymakers, all of whom scrambled in response to the idea that “AI will change everything.” Instead of resisting this claim, supposed critics of tech reinforced the deterministic outcomes of the systems while fretting that they were already too far behind.

There is power in propagating determinism using “a discourse of inevitability” to constrain the range of possible futures. To get at this, we can look to the “Social Construction of Technology” (SCOT). SCOT scholars use historical case studies to describe the process by which new innovations emerge, get adopted, and become stabilized. The most canonical example concerns the bicycle. It was not initially inevitable that the standard bicycle would have two same-sized wheels and a seat in the middle where the rider faces forward; there was a lot of “interpretive flexibility” in the early development of this technology. The creation of a “standard” bike was not determined by some abstract idea of “best.” Rather, competing actors struggled to make their vision the dominant one. In the language of SCOT, the end result of this struggle is known as “closure.” Closure does not mean that no other type of bicycle may exist. Rather, it means that one approach dominates and sets the standard for others.

Resisting Solutionism

We are in a moment of interpretive flexibility, but technologists and their financial backers are highly incentivized to create closure around their system. This is how then that technological determinism plus inevitability rhetoric gets shifted into technological solutionism. Within this logic, we must have technology to solve a problem. And of course, we will define the problem so that technology can solve it. This has been the story of how the tech industry has sold new technologies for decades.

But, notably, María Angel and I found that policymakers are going one step further. Through “duty of care” provisions, they are now arguing that since technology has caused problems, it’s now necessary for technologists to design their tools better to fix the problems. This is a form of legally required solutionism, what María and I call “techno-legal solutionism.”

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Solutionistic frames are rooted in the arrogance of determinism. Not only do they suggest that the future is known, but they suggest that a single policy or technology can create permanent closure around an issue. In the process, such an orientation fails to reckon with the ripple effects that such policies or technologies create. An interventionist frame is significantly different.

While there are plenty of hubristic doctors, the dominant contemporary paradigm in medicine is not oriented around solutions. Rather, since doctors operate probabilistically within a universe of uncertainty, they conduct interventions. Later, they follow up to evaluate the efficacy of said intervention. Although some might make predictions about the outcome of a particular intervention to calm the nerves of patients, doctors are excruciatingly aware of the possibility of side effects or other negative byproducts of their interventions. They take steps to minimize these negative outcomes, but they cannot ensure that their interventions will “solve” the problem. Medical interventions are evidence-based, but they are not deterministic. As a result, interventions must be evaluated. From there, a doctor iterates.

Shifting from a solutionistic approach to an interventionist one may seem like a game of semantics, but changing frames can support new actions. Resisting deterministic thinking is a muscle that we need to build. An interventionist approach means embracing probabilistic models since certainty is not guaranteed. An interventionist mindset also highlights the need for evaluation since, while there is a desired outcome, it is not clear that the intervention achieved that. This mindset also invites the interventionist to account for context. After all, one intervention might be more effective when the conditions are best suited for that intervention. One can also intervene at a different level by trying to shape the conditions for future interventions.

Human-in-the-Loop Solutionism

To make this concrete, let’s explore one commonly proposed “solution” to governance of AI: humans-in-the-loop. This sounds fantastic, but positioning humans in a way where they are to decide when and where to override the AI often results in them landing in a position that Madeleine Elish calls a “moral crumple zone” where they function just to absorb liability on impact.

In the 1970s, Congress approved auto-pilot for aviation, but required that pilots and co-pilots stay in the cockpit to take over in case of an emergency. Today’s pilots are glorified machine babysitters. When the machine breaks down, the probability of them successfully landing is low and pilot error is often blamed when systems break because the pilot was the last one touching the gear. But let’s look at an exception to this.

In 2009, Captain Sully successfully landed an Airbus A320 on the Hudson River in New York, saving all 155 people who were on board. After taking off from LaGuardia airport, the engines on Sully’s plane had ceased functioning because the plane flew into a flock of Canadian geese. Air traffic controllers instructed him to glide to Teterboro airport based on their models. Sully refused, arguing that he would not make it. He was instructed not to attempt a water landing because of how difficult such a landing is.

Because of his experience, Captain Sully resisted the recommendations of air traffic controllers and prioritized his own expertise over what he was being told, knowing full well that this was in violation of protocol. Unlike most pilots, Captain Sully had significant experience flying without autopilot; he had a second job retraining commercial pilots how to fly in emergencies. He also knew the New York region well. The air traffic controllers were also quite experienced and the strategies they used to support pilots were also well-honed, but neither had complete information. Captain Sully was more confident in his ability to land on the Hudson than to get to Teterboro.

After his nearly perfect landing on the Hudson, an investigation began and Sully was of course required to participate in it. Through this process, it became clear that the models used by air traffic control did not account for new construction in New Jersey; Flight 1549 would not have made it to Teterboro. Moreover, Sully argued that his inability to override computer-imposed limits that affected his glidepath created unnecessary injuries. This seemingly esoteric point flagged how contemporary pilots are presumed to be less intelligent than the machines that they fly.

As we are painfully watching in real-time, aviation is breaking down. Over decades, we’ve added AI into planes, air traffic control, and the construction of airplanes. And we’ve put disempowered humans-in-the-loop. And we have put more and more pressure on those humans. And then we’re surprised by the increase in accidents.

Humans-in-the-loop only works as a strategy if the incentives, skills, and structures are properly aligned. Currently, when humans are put into the loop on an AI system, they are primarily there to either absorb liability or uphold the mirage. Humans are the undervalued “ghost workers” as more and more supposed AI systems are rolled out with humans doing invisible labor behind the scenes (Gray and Suri, 2019). Humans are expected to override risk assessment scores, but are politically disempowered to do so (Brayne and Christin 2021).

Rather than thinking in terms of humans-in-the-loop, we need to be focused on how to properly construct an arrangement of peoples and technologies so that system degradation does not result in accidents. This requires accounting for maintenance and repair as well as looking for the vulnerabilities in the system. After all, left alone, infrastructures will break down.

Disruption is a Chess Move

A new technology is not inherently disruptive. It is disruptive if and when it is placed into an environment in a manner that benefits some people over others. The reason why the technology industry valorizes disruptive technologies is because venture capitalists and well-funded companies are well-poised to capitalize on these disruptions. In his treatise on communication power, sociologist Manuel Castells (2009) highlights how the most powerful actors are those who can arrange the networks of people, institutions, and flows of information and money to their advantage. Technologies can be introduced in a manner that disrupts existing networks, creating an opportunity for other actors to rearrange those networks in a manner that suits them. Those who are prepared for such disruptions are best equipped to respond strategically to them.

Leveraging disruption can prove quite lucrative. Not only is there money to be made on placing the right bets, but companies who are poised to leverage disruption can push for closure before competitors are able to take action. Because laws have the potential to hamper the gains from disruption, it behooves those invested in disruption to enroll policymakers into their project. This is a key lesson that the tech industry derived from Larry Lessig’s (1999) argument that code is power if and only if the market, social norms, and the law do not serve as a counterweight.

As we look to the emergent fights over AI, we need to keep our eyes wide open. This is not simply a technical debate. What we are watching is a strategic arrangement of actors and mechanisms to define a certain future as inevitable. When we play into this inevitability rhetoric and repeat industry’s deterministic orientation – even to argue that everything is bad – we do different futures a disservice. Instead, it behooves us to resist closure, eschew determinism, and eradicate “solution” from our discussions of technology. The future is not preordained. It is up to us to define it.

Il y a les images d’un monde version studio Ghibli. Et il y a Elon Musk avec un chapeau fromage.

Le monde version studio Ghibli c’est une trace documentaire qui fait l’inverse de ce que documenter veut dire. Elle déréalise, elle euphémise, elle fictionnise. Elle enlève du relief aux êtres et aux choses. Elle les installe dans un univers d’à côté. Dans une tangence.

Le monde version Elon Musk c’est à lui seul une exponentielle du grand n’importe quoi et l’asymptote d’un réel entièrement fictionné pour servir ses seuls intérêts pour autant qu’il soit lui-même en capacité de les identifier comme tels. Salut Nazi hier, chapeau fromage aujourd’hui, et demain quoi d’autre ?

On a beaucoup parlé de l’ère des Fake News et de celle des faits alternatifs. En 2018 dans l’article « Fifty Shades of Fake » publié un 1er Avril, je vous parlais de la manière dont les architectures techniques toxiques des grandes plateformes numériques se mettaient au service presque « mécanique » de cette amplification du faux et de son écho dans nos sociétés. Je martelais que « la propagation de Fake News est davantage affaire de topologie que de sociologie » ; en d’autres termes que la capacité de circulation des contenus relevant des Fake News ou des faits alternatifs, leur capacité également de percoler dans tous les espaces sociaux conversationnels, massifs ou intersticiels, médiatiques ou dialogiques, cette capacité s’explique d’abord et avant tout par la topologie et l’organisation (le « dispositif ») des espaces numériques. Et que ce n’est qu’à la marge ou en tout cas dans un second temps que l’on peut caractériser de manière causale ces circulations en les rattachant à des catégories sociologiques liées à l’âge, au niveau d’éducation ou à tout autre variable.

Sept ans plus tard, ce 1er Avril 2025, ce qui se joue est de l’ordre de la tension désormais explosive entre un écosystème numérique bâti sur la question documentaire de la trace (traces de nos données, de nos comportements, de nos navigations, de nos opinions, etc.), et un saisissement technologique et politique qui ajoute un déterminisme de l’emballement à un extractivisme souche. Et ce que l’on nomme IA  – et qui est plus précisément un ensemble d’artefacts génératifs nourris d’une incommensurable quantité de données sans considération aucune pour leur origine, leur appartenance ou leur(s) propriété(s) – ce que l’on nomme IA n’est que le dernier (et peut-être ultime) avatar à la fois de cet extractivisme et de cet emballement. Avec un point nouveau qui est celui de l’alignement total de ces technologies avec les agendas politiques de régimes tous au mieux illibéraux.

« It is a tale
Told by an idiot, full of sound and fury,
Signifying nothing. »
(Macbeth. Shakespeare.)

Poisson (mort) d’Avril. Il y a de cela quelques années, la plupart des grands groupes technologiques de la trace (de Google à Facebook) se livraient à quelques « poissons » en ce jour particulier du 1er Avril. Aujourd’hui cette pratique s’est pour l’essentiel perdue et lorsqu’elle subsiste, elle ne suscite que peu ou pas d’écho médiatique tant le rapport que nous entretenons au quotidien avec la tromperie, la duperie, le décalage, de faux et l’irréel s’est totalement transformé. Ce qui était hier une stratégie éditoriale d’exception (dire le faux) est devenu aujourd’hui un régime éditorial courant, une routine.

Le monde façon studio Ghibli. Que chacun se soit emparé de la possibilité de faire « mème » dès lors que quelques-uns se sont saisis de la nouvelle opportunité offerte de créer des images, de soi ou du monde, à la manière du studio Ghibli dans ChatGPT, n’a rien d’inédit ou d’étonnant. Chaque époque numérique a pu documenter la manière dont ces productions documentaires particulièrement fécondes étaient massivement reprises lorsqu’elles présentaient la double capacité de se mettre en scène soi-même et/ou de s’attacher à des représentations culturelles déjà prégnantes. Ainsi certains et certaines se souviendront avec moi de ces générateurs permettant de « vieillir » une photo de nous, ou de chez nous, comme à l’argentique des premiers temps photographiques ; se souviendront aussi de la reprise du portrait « Hope » d’Obama par l’artiste Shepard Fairey et de la manière dont on vit presque partout se multiplier les copies de ce portrait avec nous à la place d’Obama. Et de tant d’autres choses encore.

Aujourd’hui des biotopes numériques tout entiers sont exclusivement bâtis sur leur capacité à faire « mème », à conditionner la production de contenus à leur alignement avec des ritournelles préenregistrées, des « trends ». « Trends » ou « tendances » : des formes de facilitations virales qui devraient nous interroger non pas par leur capacité à être suivies en tant que telles dès lors qu’elles ont été « amorcées », mais par l’assignation à l’identique qu’elles produisent et qui est une forme de prophylaxie paradoxalement mortifère de diversités, d’altérités et de dissemblances. En un mot : TikTok.

Que dire d’un monde dans lequel l’esthétisation de soi (et du monde) fait aussi fonction de bascule dans d’autres régimes de vérité ? Comment « être au monde » quand la plupart des « corporations du filtre » (pour reprendre une expression d’Umberto Eco désignant les journalistes, éditeurs, bibliothécaires, etc.) qui jusqu’ici faisaient fonction d’assignation, de rappel et de construction du réel sont en train de s’effondrer pendant qu’à l’autre bout de la chaîne documentaire de l’énonciation prospère une vision du réel qui n’est plus qu’essentiellement filtrée, et ce, des filtres de déguisement que chaque application ou biotope numérique propose ou superpose à chaque dialogue ou interaction jusqu’aux filtres de travestissement qui s’accolent aux paroles politiques publiques quand elles sont portées « sous couvert » de décalage, d’humour, de cynisme ou plus simplement de … programme.

Je fais ici une différence entre la question du filtre comme « déguisement » et dans lequel l’enjeu est précisément que le destinataire puisse repérer et identifier l’effet de décalage soit par l’exagération soit par le grotesque soit par l’irréalisme produit (par exemple les filtres « oreilles de chien » dans Snapchat), et la question des filtres comme « travestissements » dans lesquels l’enjeu est cette fois de produire un effet de réel authentifiable sinon authentique, travestissements qui « agissent » de manière performative autant chez l’émetteur (avec des troubles pouvant aller jusqu’à la dysmorphophobie) que chez le récepteur devenu incapable de discernement ou propulsé dans une vallée de l’étrange dont il ne sait à quelle part de son réel rattacher l’expérience ressentie.

Se confronter à l’information sur et dans les médias sociaux numériques (mais pas uniquement) c’est donc pour beaucoup se confronter à des surimpressions permanentes et rémanentes qui oscillent entre l’esthétique Ghibli, les chapeaux fromage d’Elon Musk, ou les pulsions d’un président élu pour envahir le Groenland. Non seulement plus grand-chose ne prête à sourire mais la tentation de faire des blagues se trouve totalement distancée par le réel lui-même. Par-delà la réalité sourde de l’état réel de notre monde, de ces effondrements climatiques et de ses guerres en cours en Ukraine, à Gaza, au Yémen et ailleurs, l’actualité géopolitique internationale est une oscillation permanente entre une version documentaire d’Idiocracy et des faits totalement en phase avec la ligne éditoriale du Gorafi.

Tout cela est irréel par intention ; tout cela contribue à déréaliser pour partie notre rapport au monde et aux autres ; tout cela nous installe dans une sorte d’a-réalité, une privation de réel, une douce torpeur ; tout cela produit des formes instrumentales et instrumentalisées de tech-réalité, c’est à dire d’une réalité qui ne serait sensible qu’au travers des politiques éditoriales ou des interfaces des grandes sociétés technologiques et de leurs filtres.

Le rêve avorté du Métavers imaginé par Zuckerberg n’est pas l’essentiel. L’essentiel est de rester en capacité de discernement sur des formes avérées d’univers sociaux et informationnels qui déjà peuplent, filtrent, habitent nos univers quotidiens et qui s’y superposent en évidence.

Le monde version studio Ghibli. Et le chapeau fromage d’Elon Musk. Irréel. Déréaliser. A-réalité. Tech-réel. Et la suite. Déjà là. Tescreal.

[Mise à jour du 6 Avril] I’ve got my Ghibli. And the World is filtered-reality.