The Datafication of the Welfare State / Podatkovljenje države blaginje 

Data and algorithmic processes are increasingly an integral part of governing populations and used to categorize, profile and score individuals, households and communities, with a view to allocate services, target and identify people, and make decisions about them. In this sense, datafication is part of (re)shaping state-citizen relations, the nature of statecraft and (re)defining state models, particularly in relation to public services and welfare provision. Advancing unevenly and in diverse contexts, this trend is often underpinned by a rationale centred on efficiency, resource-saving and more ‘objective’ decision-making. 

At the same time, research has suggested that data analytics advances a society organized around risk management, in which it is assumed that it is possible to predict individual behaviour from the aggregation of data points pertaining to group traits, with the aim to both pre-empt and personalize risk. In addition, many of the tools being deployed originate in a commercial sphere, perpetuating the presence of multinational companies in the public sector, often favouring economic values rather than social, relational and personal values. These logics can be seen as the continued dismantling of the welfare state, understood in terms of a commitment to universal access, decommodification, and social solidarity. 

Moreover, the prevalence of data science as developed and practiced by a few dominant global players raise questions about the standardization of governance and statecraft. By fleshing out these issues, this talk will reflect on transformations brought about by data processes in the public sector and across social life, and contextualise these in terms of different value-systems and visions for how society should be organised.

Podatki in algoritemski procesi so vedno bolj integralen del vladanja prebivalstvu. Uporabljeni so za kategoriziranje, profiliranje in razvrščanje posameznikov, gospodinjstev in skupnosti z namenom dodeljevanja storitev, prepoznavanja in  identifikacije ciljnih skupin in posameznikov ter sprejemanja odločitev o njihovih življenjih. V tem smislu je podatkovljenje del (pre)oblikovanja odnosov med državami in državljani, narave državnosti in (pre)oblikovanja državnih modelov, še posebej v navezavi na javne storitve in socialno varnost. Ta trend, ki napreduje neenakomerno in v raznolikih kontekstih, pogosto podpira usmeritev k učinkovitosti, varčevanju in bolj “objektivnemu” odločanju. 

Raziskave so pokazale, da podatkovna analitika razvija družbo, osredotočeno na upravljanje s tveganji. Tak pristop predpostavlja, da je obnašanje posameznika mogoče napovedati z zbiranjem podatkov, ki se nanašajo na lastnosti posameznih skupin. Namen tega je predvidevanje in personalizacija tveganj. Poleg tega številna uporabljena orodja izvirajo iz komercialne sfere ter vnašajo in ohranjajo prisotnost multinacionalk v javnem sektorju. Pogosto so naklonjena  predvsem ekonomskim, ne pa družbenim, relacijskim in osebnim vrednotam. Tovrstne logike lahko razumemo v kontekstu razgradnje socialne države, ki temelji na univerzalnemu dostopu, dekomodifikaciji in družbeni solidarnosti. 

Podatkovna znanost se razvija in prakticira s strani maloštevilnih, dominantnih in globalnih akterjev, kar odpira vprašanja standardizacije vladanja in državnosti. Predavanje bo mislilo transformacije, ki so jih v javni sektor ter družbeno življenje prinesli podatkovni procesi. Te bodo kontekstualizirane v smislu različnih sistemov vrednot in vizij, kako naj bo družba organizirana.

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