While we think of our francophone uniqueness as an asset, especially in the battle for attention, and in the greater one for diversity of cultural and linguistic expression on the internet, machine language and algorithms see this uniqueness as a weakness or a deficiency. The amount of available francophone content does not achieve a true critical mass that would trigger a network effect. If, as defined by l’Office québécois de langue française (OQLF), discoverability is “the potential for a piece of content, a product or a service to capture the attention of a web user in a way that helps discover new or different content”, then the potential for discoverability of francophone content is, by default, lesser, or insufficiently interesting to fulfil the criteria of regional or semantic algorithmic associations necessary to trigger the recommendation mechanisms that other, similar content enjoys, even if this is only with regard to the content’s language of origin.
In this context, it is worrisome to observe that from the point of view of the representation of diversity of identities and cultures online, the relational cultural identity that one should be able to enjoy as a francophone belonging to an international community of francophone web users consuming French-language content online is fraying and mutating progressively into a ‘refuge identity’, that of a threatened and resistant minority seeking to remain visible, like a drop of water in the immense ocean of the web.
A study published in June of 2017 by l’Observatoire de la diversité linguistique et culturelle dans l’Internet found that French is the fourth language of the internet, with 6.5% of content produced, behind English (32%), Chinese (18%) and Spanish (8%). Given that the percentage of francophone web users is estimated to be 5.4%, it is tempting to think that there is a very good productivity ratio of francophone content, at 6.5%. But in reality, the challenge that these statistics reveal lies less in the level of production of francophone content than in its discoverability and effective online consumption.
The problem that arises with a certain acuteness is that the dominant platforms (Facebook, Amazon, Apple, Netflix, Google/YouTube and Spotify) which have imposed themselves as the new global suppliers of cultural content, have also begun to develop, produce and distribute their own content (for example Netflix Originals); and these constitute an ‘oligopoly of discoverability’ with the algorithmic power to engineer and orient global cultural consumption.
When we talk about discoverability, what is important is no longer just the characteristics or the intrinsic potential of the content to be discovered, or the ability to learn about new content. Discoverability must no longer be examined solely as the process of a meeting between the work and its audience. This approach masks or minimizes the effects of the process itself, through which the public decides which content or cultural products to consume, to the detriment of other choices.
What we are seeking to demonstrate here is the fact that the discoverability process is increasingly programmed, i.e. controlled and strongly predetermined by the platforms through a combination of their editorial logic, their personalized recommendation systems and the commercial and marketing strategies linked to their business models. This ‘programmed discoverability’ is dictated by a whole set of criteria and algorithmic criteria and rules, but also by the basic conditions of use, distribution and exploitation of content to which creators and producers are subjected, and to which users and subscribers to these platforms contribute (particularly through their usage data, which helps to improve the performance and precision of the algorithms). With ‘programmed discoverability’, we are no longer simply in the era of recommendation: we are entering into the era of meta-recommendation, i.e. the recommendation of that which must be a priori recommendable.
It seems that programmed discoverability has put an end to the multiple perspectives that we enjoyed in serendipitously searching the web, as we have done since the dawn of the web, with its multitude of intuitive hyperlinks. Is it really still possible today to discover content on the web purely by chance, without a preceding search or online activity being linked to the content discovered? In reality, the web is no longer fertile terrain for discovery by ‘happy accident’. When we look at it closely, it seems that impromptu discovery of new content is always linked to the history and aggregation of the traces of our previous navigation, minimal as they might be, and to our usage of various applications and digital platforms that are always scrutinizing our online behaviour.