Organising for "social good" in calculative collective markets : the case of digital social innovations in Europe
Résumé
Previous research reveals that one of the problems in social innovation is replication and scaling of social programs in different sites. We show through cases that while algorithms make replication easier due to advantages of speed and scale through ICTs, there is a trade-off. The same processes that make algorithms "efficient" for scaling can pose a problem for digital social innovation (DSI) effectiveness in solving problems, mainly by 1. reducing the extent to which algorithms can be adapted to local context, and 2. by allowing DSI developers to make them obscure. To address this tradeoff from a theoretical perspective, and relate it to the types of DSIs identify, we take DSI spaces as "calculative collective devices" (Callon and Muniesa, 2005). In the paper we take each of the components of calculative markets (goods, agencies, encounters) and through detailed illustrative cases apply them to the context of DSIs. We show how in network platforms, offline interactions with online will reduce asymmetry in calculative agency, by permitting a more refined process of singularisation by audiences. Second, we show that the extent to which open source platforms can reduce this asymmetry depends on the digital skills, civic engagement levels, and coordination costs. Third, in global platforms, asymmetry in calculative agencies tend to be higher, due to heterogeneity of audiences.